Department of Electronics and Electrical Engineering
Indian Institute of Technology Guwahati
Guwahati-781039, India

Syllabus (Elective courses) :

EE 610 Fundamentals of VLSI CAD 3-0-0-6

Course contents:

Matrices: Linear dependence of vectors, solution of linear equations, bases of vector spaces. orthogonality, complementary orthogonal spaces and solution spaces of linear equations. Graphs: representation of graphs using matrices; paths, connectedness; circuits, cutsets, trees; fundamentals circuit and cutset matrices; voltage and current spaces of a directed graph and their complementary orthogonality. Algorithms and data structures: efficient representation of graphs; elementary graph algorithms involving BFS and DFS trees, such as finding connected and 2-connected components of a graph, the minimum spanning tree, shortest path between a pair of vertices in a graph; Algorithms for VLSI Physical Design, Synthesis, Circuit Simulation and Digital Design Automation. Algorithms for Design Automation using FPGA/CPLD, Fault Tolerant Systems, VLSI Testing.


    1. K. Hoffman and R.E. Kunze, Linear Algebra, Prentice Hall(India), 1986.
    2. N. Balabanian and T.A. Bickart, Linear Network Theory; Analysis, Properties, Design and Synthesis, Matrix Publishers, Inc., 1981.
    3. T. Cormen, C.Leiserson and R.A. Rivest, Algorithms, MIT press and McGraw Hill,1990.
    4. N. Shervani, Algorithms for VLSI Physical Design Automation, 3rd Edn., KluwerAcademic Publishers, 1998
    5. W. J. McCalla, Fundamentals of Computer-Aided Circuit Simulation, KluwerAcademic Publishers, 1987
    6. G. De Micheli, Synthesis and optimization of Digital Circuits, Tata McGraw Hill, 2003.
    7. S. H. Gerez, Algorithms for VLSI Design Automatiom, John Wiley & Sons, 1999.

EE 611 Organic Semiconductor Devices 3-0-0-6

Course Contents:
Introduction to organic semiconductor devices; Electronic Transitions, Excitons, and Energy transfer; Charge generation and recombination mechanisms; Polaron and Disorder models for charge transport; Space charge and Trap limited currents; Charge injection at metal/organic interface; Organic light emitting diodes (OLEDs); Bilayer, Bulk-heterojunction, Inverted, and Tandem organic photovoltaic (OPV) devices; Carrier loss mechanisms in OPVs; Nanomorphology; Hybrid Perovskite solar cells and LEDs; Top and bottom contact organic thin film transistors (OTFTs); Display driver circuits; Operating principles of organic lasers and memory devices; Device degradation mechanisms and Stability testing methods; Organic thin film deposition techniques and Overview of various printing technologies.

[1]. Suganuma Katsuaki, Introduction to Printed Electronics, Springer, 2014.
[2]. Stergios Logothetidis, Handbook of Flexible Organic Electronics - Materials, Manufacturing, and Applications, 1st Ed., Woodhead Publishing, 2014.
[3]. Eugenio Cantatore, Applications of Organic and Printed Electronics: A Technology Enabled Revolution, Springer, 2012.
[4]. Wolfgang Brütting and Chihaya Adachi, Physics of Organic Semiconductors, 2nd Ed., Wiley-VCH, 2012.
[5]. Anna Köhler and Heinz Bässler, Electronics Processes in Organic Semiconductors - An Introduction, 1st Ed., Wiley-VCH, 2015.
[6]. Wenping Hu, Organic Optoelectronics, 1st Ed., Wiley-VCH, 2013.
[7]. Sam-Shajing Sun and Larry R. Dalton, Introduction to Organic Electronic and Optoelectronic Materials and Devices, 2nd Ed., CRC Press, 2015.
[8]. Franky So, Organic Electronics: Materials, Processing, Devices, and Applications, CRC Press, 2010.

EE 613 Radio Frequency Integrated Circuits 3-0-0-6

Course contents:

Fundamentals of RF circuits and systems: Duplexing, FDMA, dB, dBm, Voltage gain, Channel, ACR, AACR, Noise factor, NF of a cascaded system, Sensitivity, HD, Gain compression, P1dB, Cross modulation, Inter modulation, IM3, IIP3, SFDR, Transmit mask

Transmitter and Receiver architectures: Review of modulation schemes, Receiver architectures, Transmitter architectures

Passive and active components for CMOS RFIC: Review of MOSFET, RF transistor layout, CMOS process, Capacitors, Varactors, Resistors, Inductors, Transformers, Transmission lines Resonance, Matching, S-parameters, etc. Noise in electrical circuits and NF calculations, Two port noise theory

Low Noise Amplifiers: Resistive terminated CS and CG LNA, Inductive degenerated LNA, Shunt feedback LNA, Noise canceling LNAs, Linearity improvement techniques

Power Amplifiers: Basics and Class A, B, C, D, E, F and other configurations, Power combining, Linearity improvement techniques

Mixers: Specifications, NL system as a mixer, Active mixers, Passive mixers

Oscillators: Introduction, LC Oscillators, Phase noise, Introduction to PLLs; Type-I PLLs, Charge pump PLLs: Mathematical model, Design issues and Phase noise

Frequency synthesizers: Integer N synthesizers, Dividers,

Texts/ References:

1) B. Razavi, "RF Microelectronics", 2nd Ed., Pearson, 2012.
2) Thomas H. Lee, "The design of CMOS radio-frequency integrated circuits", 2nd Ed., Cambridge University Press, 2004.

EE 620 Image Processing 3-0-0-6

Course Contents:
Human visual system and image perception; Monochrome and colour vision models;Image acquisition and display: Video I/O devices; Standard video formats; Imagedigitization, Display and storage; 2-D signals and systems; Image transforms: 2D-DFT,DCT, KLT, Harr transform and discrete wavelet transform; Image enhancement:Histogram processing, Spatial-filtering, Frequency-domain filtering; Image restoration:Linear degradation model, Inverse filtering, Wiener filtering; Image compression: Lossyand lossless compression, Entropy coding, Transform coding, Subband coding; Imagecompression standards: Video compression- motion compensation, Video compressionstandards; Image analysis: Edge and line detection, Segmentation, Feature extraction,Classification; Image texture analysis; Morphological image processing: Binarymorphology- Erosion, Dilation, Opening and closing operations, Applications, Basic grayscale morphology operations; Colour image processing: Colour models and colourimage processing.


  1. A. K. Jain, Fundamentals of Digital Image processing, Pearson Education, 2009.
  2. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Pearson Education, 2008.
  3. R. C. Gonzalez, R. E. Woods and S. L. Eddins, Digital Image Processing using MATLAB, Pearson Education, 2004.
  4. W. K. Pratt, Digital Image Processing, John Wiley & Sons, 2006.
  5. S. Ahmed, Image Processing, McGraw -Hill, 1994.
  6. S. J. Solari, Digital Video and Audio Compression, McGraw-Hill, 1997

EE 621 Computer Vision 3-0-0-6

Course Contents:

Image formation and image models; Image filtering; Lines, Blobs, Edges and boundarydetection; Representation of 2-D and 3-D structures; Bayes decision theory for patternrecognition; Supervised and unsupervised classifications; Parametric and nonparametricschemes; Clustering for knowledge representation; Applications of neural networks andfuzzy logic in pattern recognition; Feature extraction in images; Texture analysis andclassification; Image segmentation; Optical character recognition; 2-D and 3-D objectrecognition; Surface extraction from monocular images; Stereo image pair analysis; Optical flow and 3-D motion analysis.


    1. A. K. Jain, Fundamentals of Digital Image processing, Pearson Education, 2009.
    2. D. A. Forsyth and J. Ponce, Computer Vision, A Modern Approach, Pearson Education, 2003.
    3. D. H. Ballard and C. M. Brown, Computer Vision, Prentice Hall, 1982.
    4. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis, John Wiley, 2006.
    5. R. Jain, R. Kasturi and B. G. Schunck, Machine Vision, McGraw-Hill, 1995.
    6. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Addison-Wesley, 2008.
    7. R. Schalkoff, Pattern Recognition – Statistical, Structural and Neural Approaches, John Wiley, 2007.

EE 622 Biomedical Signal Processing 3-0-0-6

Contents: Sources of bioelectric potential, resting potential, action potential, propagation of action potentials in nerves; rhythmic excitation of heart; ECG: Pre-processing, wave form recognition, morphological studies and rhythm analysis, automated diagnosis based on decision theory, ECG compression, Evoked potential estimation. EEG: Evoked responses, averaging techniques, pattern recognition of alpha, beta, theta and delta waves in EEG waves, sleep stages, epilepsy detection.EMG: Wave pattern studies, biofeedback. application of signal processing techniques such as linear prediction, lattice - filtering & adaptive signal processing for extraction of physiological parameters; introduction to wavelets & time frequency models and their applications to heart sounds, fetal ECG & vesicular sound signals; speech production model, inverse filtering techniques for extraction of vocal tract parameters, glottal inverse filtering; electroglottograpic signals; signal processing techniques for detection of pathologies in speech production system; speech synthesis and speech recognition in diagnostic and; therapeutic applications; medical imaging techniques: CT scan, ultrasound, NMR and PET. Experiments are based on acquisition of biomedical signals and implementation of algorithms covered in the course to charcterise these signals.


    1. E.N. Bruce, Biomedical Signal Processing and Signal Modelling, John Wiley and Sons, 2001.
    2. W. J. Tompkins, ed., Biomedical Signal Processing; Prentice Hall, 1995.
    3. M. Akay: Wavelets and Time frequency methods for Biomedical signal Processing; IEEE Press, 1995.
    4. L. Rabinar: Digital Processing of speech signals; Prentice Hall, 1978.
    5. A. C. Guyton: Human Physiology; Prism International, 1991.

EE 623 Speech Signal Processing and Coding 3-0-0-6

Contents: Introduction: speech production and perception, information sources in speech, linguistic aspect of speech, acoustic and articulatory phonetics, nature of speech, models for speech analysis and perception; Short-term processing: need, approach, time, frequency and time-frequency analysis; Short-term Fourier transform (STFT): overview of Fourier representation, non-stationary signals, development of STFT, transform and filter-bank views of STFT; Cesptrum analysis: Basis and development, delta, delta-delta and mel-cepstrum, homomorphic signal processing, real and complex cepstrum; Linear Prediction (LP) analysis: Basis and development, Levinson-Durbin’s method, normalized error, LP spectrum, LP cepstrum, LP residual; Sinusoidal analysis: Basis and development, phase unwrapping, sinusoidal analysis and synthesis of speech; Speech coding: Need and parameters, classification, waveform coders, speech-specific coders, GSM, CDMA and other mobile coders; Applications: Some applications like pitch extraction, spectral analysis and coding standard.

1. L.R. Rabiner and R.W. Schafer, Digital Processing of Speech Signals Pearson Education, Delhi, India, 2004
2. J. R. Deller, Jr., J. H. L. Hansen and J. G. Proakis Discrete-Time Processing of Speech Signals, Wiley-IEEE Press, NY, USA, 1999.
3. D. O’Shaughnessy, Speech Communications: Human and Machine, Second Edition,University Press, 2005.
4. T. F. Quatieri, “Discrete time processing of speech signals”, Pearson Education, 2005.
5. L. R. Rabiner, B. H. Jhuang and B. Yegnanarayana, “Fundamentals of speech recognition”, Pearson Education, 2009.

EE 624 Speech Technology 3-0-0-6

Contents: Applications, pattern recognition, feature extraction, modeling, testing; Speech recognition: Objective, issues, block diagram description, classification, development of speech recognition system using vector quantization (VQ), dynamic time warping (DTW), Hidden Markov Model (HMM) and Neural networks (NN); Speech synthesis: Objective, issues, block diagram description, classification, development of speech synthesis system using articulatory, parametric, concatenative and HMM based approaches; Speaker recognition: Objective, issues, block diagram description, classification, development of speaker recognition system using VQ, DTW, GMM, NN and HMM; Speech enhancement: Objective, issues, block diagram description, classification, enhancement of noisy speech, reverberant speech enhancement and multi-speaker speech processing.

1. L. R. Rabiner, B. H. Jhuang and B. Yegnanarayana, “Fundamentals of speech recognition”, Pearson Education, 2009.
2. J. R. Deller, Jr., J. H. L. Hansen and J. G. Proakis Discrete-Time Processing of Speech Signals, Wiley-IEEE Press, NY, USA, 1999.
3. D. O’Shaughnessy, Speech Communications: Human and Machine, Second Edition,University Press, 2005.
4. J. Benesty, M. M. Sondhi and Y. Huang, “Handbook of speech processing”, Springer, 2008.

EE 626 Pattern Recognition and Machine Learning 3-0-0-6

Course Contents:

Introduction: Problem framing, feature selection, dimensionality reduction using PCA and other methods; Discriminative classifiers: LDA, Multi-layer perceptron, backpropagation, SVM; Unsupervised learning: Clustering, Vector Quantization, Kohonen Map, EM Algorithm; Generative models: Definition and characteristics, probabilistic graphical models, density estimation in learning; Combining classifiers: Advantages, boosting, hierarchical classifiers, and issues; Selected special topics such as manifold learning and case studies.


    1. S. Marsland, Machine Learning: An Algorithmic Perspective, Chapman & Hall/CRC, 2009.
    2. R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification, 2nd Edn., Wiley India, 2007.


    1. C. . Bishop, Pattern Recognition and Machine Learning (Information Science and Statistics), Springer, 2006.
    2. I. H. Witten, Data Mining: Practical Machine Learning Tools And Techniques, 2nd Edn., Elsevier India, 2008.

EE 627 Biometrics 3-0-0-6

Course Content:
Introduction: History and Overview of Biometrics, Applications of Biometrics and Future Trends; Image Processing for Biometric Applications; Biometrics as a Pattern Recognition System; Biometric System Modalities: Face Recognition, Fingerprint Recognition, Iris Recognition, Voice/Speaker recognition, Hand Geometry Recognition, Gait Recognition, Signature Recognition; Additional Biometric Traits; Biometric System Design and Performance Evaluation; Multi-modal Biometric Systems; Biometric Security; Privacy and Ethical Issues.

Texts/ References:

  1. Anil K. Jain, Arun A. Ross and Karthik Nandakumar, “Introduction to Biometrics”, Springer, 2011, ISBN 978-0-387-77326-1.
  2. J. Ashbourn, “Biometrics: Advanced Identity Verification: The Complete Guide”, Springer, 2000, ISBN-13: 978-1852332433.
  3. J.L. Wayman, A.K. Jain, D. Maltoni and D. Maio, “Biometric Systems: Technology, Design and Performance Evaluation”, Springer, 2005, ISBN 978-1-84624-064-1.
  4. D. Maltoni, D. Maio, Anil K. Jain and Salil Prabhakar “Handbook of Fingerprint Recognition”, Springer, 2009, ISBN 978-1848822535.
  5. Stan Z. Li and Anil K. Jain “Handbook of Face Recognition”, Springer; 2nd ed., 2011, ISBN 978-0856289314.

EE 629 Multimedia Security: Methodologies for content access control, tracking and authentication 3-0-0-6

Course Contents:

Digital rights management (DRM) framework: Requirements of a DRM system,Architectures, Dimensions to content protection: Tracing (fingerprinting), authentication,Encryption, Key management and access control.

Multimedia fingerprinting: Fingerprinting basics, Marking assumption, Collusion attack,Frame proof and anti-collusion codes; Combining fingerprint modulation with coding:Introduction to coded fingerprint modulation, Semi-fragile fingerprinting; Multicastfingerprinting problem: Bandwidth security tradeoff; Efficient security architectures:WHIM, Watercasting, Chameleon cipher; Joint fingerprinting and decryption (JFD)framework; Fingercasting.

Multimedia encryption: Traditional symmetric key ciphers, Shannon’s principles ofconfusion and diffusion; Overview of Advanced Encryption Standard (AES); Block andstream ciphers; Information theoretic secrecy; Multimedia encryption: Concept of layering,Multimedia compression technologies and standards; Principles for selective encryption;Image and Video encryption schemes: Chaotic maps, Transform domain encryption,Huffman tree mutation; Streaming media encryption: Scalable video protection; Keymanagement and distribution schemes: Key management for IP Multimedia: Public key methods, Key distribution by data embedding; Key exchange in multicast groups: Keyrefresh problem, Logical Key Hierarchy (LKH); Key distribution for fine grained accesscontrol.

Content authentication techniques: Data authentication, One way hash functions,Message authentication codes (MACs); Multimedia authentication: Perceptual hashes;Parameterization; Watermarking based authentication: Notion of semi-fragility,Construction and design of semi-fragile watermarks; Example: Principles of videoauthentication: Scalability issues, packet loss, post-processing.

Privacy preserving protocols: Zero knowledge protocols, Anonymous fingerprinting,Public key watermarking, Non-perfect secret sharing constructions for anonymousfingerprinting with shared access control.


    1. W. Zeng, H. Yu and C. Lin, Multimedia Security Technologies for Digital Rights Management, Elsevier, UK, 2006.
    2. K. Karthik and D. Hatzinakos, Multimedia Encoding for Access Control With Traitor Tracing: Balancing Secrecy, Privacy and Traceability, VDM Verlag, ISBN: 978-3-8364-3644-0, Germany, 2008.
    3. B. Furht and D. Kirovski (Eds.), Multimedia Security Handbook, CRC press, U.S., 2005.
    4. B. Schneier, Applied Cryptography: Protocols, Algorithms and Source Code in C, 2nd EdITION, Wiley India, 2007 (Reprint).

EE 630 Mobile Communication 3-0-0-6

Course Contents

Evolution of mobile radio communication; Different generations of wireless communication and their technical specifications; Cellular concept: frequency reuse, channel assignment, handoff, interference, i mproving system capacity and cell coverage, radio trunking; Mobile radio propagation: free space propagation, reflection, diffraction, scattering, link budget design; Fading: multipath propagation, Doppler shift, impulse response model,multipath parameters, statistical models for multipath propagation; Mitigation of fading effects: equalization, diversity, channel coding; Transmitter and receiver techniques: modulation up to GMSK, line coding, pulse shaping, OFDM; Multiple access: FDMA, TDMA, SSMA, SDMA.


    1. T. S. Rappaport, Wireless Communications: Principles and Practice, Pearson Education, 2004.
    2. S. Haykin and M. Moher, Modern Wireless Communications, Pearson Education, 2005.


    1. W. H. Tranter et. al., Principles of Communication Systems Simulation withWireless Applications, Pearson Education, 2004.
    2. A. Mitra, Lecture Notes on Mobile Communication[online], QIP Section, IIT Guwahati, 2009.

EE 632 Advanced Topics in Communication Systems 3-0-0-6

Course Contents:

Ultra wideband (UWB) communication systems: UWB concepts, advantages and challenges, single band versus multiband, FCC emission limits, UWB applications; UWB sources and antennas: UWB pulse generation, UWB antennas; Pulse-detection and multiple-access techniques: Conventional pulse-detection techniques, pulse modulation and detection techniques, UWB multiple-access techniques; Interference issues: Interference with WLAN, cellular & GPS. Multiple-Input, Multiple-Output (MIMO) wireless communication: Basic MIMO model, MIMO capacity in fading channels, Diversity multiplexing trade off, Space-time code for MIMO wireless communication. Software Define Radio (SDR): Characteristics and benefits of a software radio, design principles of software radio, enhanced flexibility with software radios, receiver design challenges.

1. K. Siwiak and D. McKeown, Ultra-Wideband Radio Technology, John Wiley and Sons Limited, 2004.
2. S. Haykin and M. Moher, Modern Wireless Communication, Pearson Education, 2005.
3. Jeffrey H. Reed, Software Radio: A Modern Approach to Radio Engineering, Prentice Hall, May 2002
4. Faranak Nekoogar, Ultra-Wideband Communications: Fundamentals and Applications, Prentice Hall, 2005.
5. C. Oestges and B. Clerckx, MMIO Wireless Communications, 1st Ed, 2007.
6. Paul Burns, Software Defined Radio for 3G, Artech House Inc., 2003.

EE 633 Error Control Codes 3-0-0-6

Course Contents:

Block codes and convolutional codes: Introduction to groups and vector spaces;Generator and parity check matrices, Dual codes, Hamming codes, General properties oflinear codes and different coding bounds, Ring and finite fields, Encoding and decodingof cyclic codes, BCH codes and RS codes-construction, properties and decoding, Trellisrepresentations of convolutional codes and decoding using Viterbi algorithm; Iterative Codes: LDPC Codes, Tanner graph, Cycles, irregular codes, Message-passing decoderand density evolution; Turbo codes: Definition, BCJR algorithm and EXIT charts;Network Codes: Introduction, The Max-Flow bound, Single-source Linear NetworkCoding-Acyclic and Cyclic networks, Multi-source Network Coding.


    1. W.E Ryan and S Lin, Channel Codes-Classical and Modern, Cambridge University Press,2009
    2. R.W Yeung, Information Theory And Network Coding, Springer, 2008
    3. F.J. MacWilliams and N.J.A Sloane, The Theory of Error-Correcting Codes, Elsevier Science, 1988
    4. D Lun and T Ho, Network Coding - An Introduction, Cambridge University Press, 2008

EE 634 MIMO Wireless Communications: Fundamentals and Advances 3-0-0-6

Course contents:

Introduction: Diversity-multiplexing trade-off, transmit diversity schemes, advantages and applications of MIMO systems
Analytical MIMO channel models: Uncorrelated, fully correlated, separately correlated and keyhole MIMO fading models, parallel decomposition of MIMO channel.
Power allocation in MIMO systems: Uniform, adaptive and near optimal power allocation.
MIMO channel capacity: Capacity for deterministic and random MIMO channels, Capacity of i.i.d., separately correlated and keyhole Rayleigh fading MIMO channels.
Space-Time codes: Advantages, code design criteria, Alamouti space-time codes, SER analysis of Alamouti space-time code over fading channels, Space-time block codes, Space-time trellis codes, Performance analysis of Space-time codes over separately correlated MIMO channel, Space-time turbo codes.
MIMO detection: ML, ZF, MMSE, ZF-SIC, MMSE-SIC, LR based detection
Advances in MIMO wireless communications: Spatial modulation, MIMO based cooperative communication and cognitive radio, multiuser MIMO, cognitive-femtocells and large MIMO systems for 5G wireless.

Texts/ References:

1. B. Clerckx and C. Oestges, MIMO wireless networks, Elsevier Academic Press, 2nd ed., 2013.
2. T. M. Duman and A. Ghrayeb, Coding for MIMO communication systems, John Wiley and Sons, 2007.
3. N. Costa and S. Haykin, Multiple-input multiple-output channel models, John Wiley & Sons, 2010.
4. J. Choi, Optimal Combining & Detection, Cambridge University Press, 2010.
5. A. Chokhalingam and B. S. Rajan, Large MIMO systems, Cambridge University Press, 2014.

EE 635 Network Coding and Applications 3-0-0-6

Course contents:

Theoretical frameworks for network coding: Max-flow min-cut theorem, routing capacity of a network, the main theorem of network multicast; linear, algebraic and random network coding, network coding for non-multicast networks; Network coding applications: Content distribution, network coding for wireless networks, security, network error correcting codes, distributed storage systems.

Texts/ References:

1. C. Fragouli & E. Soljanin, “Network Coding Fundamentals,” NOW Publishers, 2007.
2. C. Fragouli & E. Soljanin, “Network Coding Applications,” NOW Publishers, 2008.
3. T. Ho, “Network Coding: An Introduction,” Cambridge University Press, 2008.

EE 636 Selected Topics in Information Theory 3-0-0-6

Course Content:
Rate Distortion theory: Calculation of the rate distortion function, achievability of the rate distortion function, computation of the rate distortion function; Information Theory and Statistics: Sanov’s theorem, conditional limit theorem, Chernoff-Stein lemma, Fisher Information; Maximum Entropy: Spectrum estimation, Burg’s maximum entropy theorem; Universal Source Coding: Method of types, Arithmetic coding, Lempel-Ziv coding; Network Information Theory: Multiple-access Channel, encoding of correlated sources, broadcast channels, relay channel; Information Theory and Portfolio Theory: Optimal Investment and information theory, Universal Portfolios and data compression.

Texts :

1. Cover & Thomas, “Elements of Information Theory”, 2nd ed, Wiley, 2006.
2. Csisz´ar & K¨orner, “Information Theory: Coding Theorems for Discrete Memoryless Systems”, Cambridge university press, 2011.


1. El Gamal, Y.-H. Kim, “Network Information Theory”, Cambridge University Press, 2011.
2. Robert M. Gray, “Entropy and Information Theory”, Springer, 1988.

EE 637 Green Wireless Sensor Networks 3-0-0-6

Course Content:
Introduction; Wireless sensor network: applications and scenarios, classification, characteristics, issues; Wireless sensor network design requirements: System requirements, device requirements; Sensor network architecture: systems infrastructure including QoS and energy management; Sensor node architecture: major energy consuming units; Communication Standards Used: IEEE 802.15.4, ZigBee; Component-level energy optimization techniques; System-level energy optimization techniques: Dynamic Power Management, Dynamic Voltage-Frequency Management, Code optimization for energy saving, Computation-Communication energy trade-off, Network-level energy optimization; Case studies: Source encoding, channel encoding for energy optimization;

Texts / References :

1. H Venkataraman and G M Muntean, (Eds.), Green mobile devices and networks: energy optimization and scavenging techniques, CRC Press, 2012.
2. I M M El Emary, S Ramakrishnan, Wireless Sensor Networks: From Theory to Applications, CRC Press 2016.
3. I F Akyildiz, M C Vuran, Wireless Sensor Networks, Wiley, 2010.
4. C S Raghavendra, K M Sivalingam, T Znati (Eds.), Wireless Sensor Networks, 2004.
5. M Ilyas, I Mahgoub, Smart Dust: Sensor Network Applications, Architecture and Design, CRC Press, 2006.
6. K Kaspersky, Code Optimization: Effective Memory Usage, A-List Publishing, 2003.
7. J. Rabaey, Low Power Design Essentials, Springer Publishing Company, Inc., 2009.
8. W Wolf, Computers as Components: Principles of Embedded Computing System Design, Second Edition, Morgan Kaufmann, 2008.
9. L Benini and G De Micheli, Dynamic Power Management: Design Techniques and CAD Tools, Kluwer Academic Publishers, 1997.

EE 638 Massive MIMO for 5G Communications: Design and Analysis 3-0-0-6

Course Contents

Introduction: Evolution of cellular systems from 1G to 4G and the principles underlying different generations, Engineering requirements and application scenarios for 5G, Role of massive MIMO as a key 5G solution, Characteristics and benefits of massive MIMO systems, signal and channel models, Differences with respect to point-to-point MIMO and multiuser MIMO, time division and frequency division duplex modes of operation; Mathematical preliminaries: Circular symmetric complex Gaussian random vectors, Few random matrix results, Wishart distributions, detection and estimation in additive Gaussian noise; Capacity and capacity bounding techniques: Fading channels, capacity for point-to-point scalar channels, point-to-point MIMO channels, and multiuser MIMO channels, discussion on few capacity bounding tools; Single and multiple cell analysis: Uplink training and channel estimation, uplink data transmission, zero-forcing and maximum ratio detection, downlink data transmission, zero-forcing and maximum ratio precoding, derivation of spectral efficiency results; pilot contamination and its effects, asymptotic analysis; Power control in massive MIMO systems: Single cell, multiple cells, max-min fairness; Propagation channels: Conditions for favorable propagation, independent Rayleigh fading, uniformly random line-of-sight channels; Case studies: Examples of single and multiple cell deployment; Recent research results: Pilot Decontamination, Effects of hardware impairments, Massive MIMO with FDD operation, Cell-free Massive MIMO; Other potential 5G technologies such as device to device communications and applicability of massive MIMO to small cells and mmwave communications.


1. T. L. Marzetta, E. G. Larsson, H. Yang, and H. Q. Ngo, Fundamentals of Massive MIMO, Cambridge University Press, 2016
2. D. Tse and P. Viswanath, Fundamentals of Wireless Communication, Cambridge University Press, 2005
3. R. S. Kshetrimayum, Fundamentals of MIMO Wireless Communications, Cambridge University Press, 2017
4. W. Xiang, K. Zheng, and X. Xuemin, 5G Mobile communications, Springer, 2017
5. J. Rodriguez, Fundamentals of 5G Mobile Networks, John Wiley & Sons, 2015
6. H. Yang and T. S. Quek, Massive MIMO meets Small Cell: Backhaul and Cooperation, Springer, 2016.

EE 643 Silicon Photonics 3-0-0-6

Course Contents

Introduction to Silicon Photonics; Fundamentals of guided waves; Silicon Photonic Waveguides; Coupling to waveguides; Waveguides loss mechanisms; Optical Processes; Device preparation and characterization; Light Emitters in Si; Silicon Photodetectors; Waveguide based devices; Polarization and Integration; Optical Modulators in Silicon Photonic Circuits; Silicon Photonic Applications.


1. D. Inniss and R. Rubenstein, Silicon Photonics Fueling the Next Information Revolution, Elsevier 2017
2. L. Pavesi and D. J. Lockwood, Silicon Photonics III Systems and Applications, Springer 2016
3. G. T. Reed and A.P. Knights, Silicon Photonics: An Introduction, Wiley 2004
4. G. T. Reed, Silicon Photonics: The state of the art, Wiley 2008
5. L. Pavesi and D. J. Lockwoodt, Silicon Photonics, Springer 2004
6. L Pavesi and G Guillot, Optical Interconnects: The Silicon Approach, Springer 2006
7. M J Deen and P K Basu, Silicon Photonics: Fundamentals and Devices, Wiley 2012
8. H Zimmermann, Integrated Silicon Optoelectronics, Springer 2010

EE 644 Plasmonics, nanophotonics and metamaterials 3-0-0-6

Course Contents:

Introduction; Light–matter interaction: Local field approximation, Constitutive relations, Dispersion in materials, Kramers–Kronig relationship; Two level system, Lorentz model; Metals, semiconductors and dielectrics; Scattering from planar interfaces, microstructures and nanostructures; Composite materials, effective medium theory. Introduction to photonic crystals: Electromagnetic wave in periodic potential; Applications of photonic crystals for omni-directional reflection; Sharp waveguide bends; Light localization; Super-prism effects and photonic crystal fibers; Silicon Nanophotonics — A current status. Plasmonics: Metal optics—An introduction; Surface plasmon excitation; Localized surface plasmon and applications. Light interaction with 0, 1 and 2 dimensional metallic nanostructures; Guiding and focusing of light (below the diffraction limit); Optical nanoantennas; Technology of the future—Graphene photonics; Plasmonics and optoelectronics. Metamaterials: Electric and magnetic metamaterials; Negative refractive index; Super-lens and hyper-lens; Transformation optics, invisibility cloak, and extraordinary transmission; Metamaterial fabrication/simulation technologies; New plasmonic materials; Tunable plasmonic metamaterials and metadevices such as electrotuneable switchable window/mirror, nanoplasmonic optical filters and sensors.

Pre-requisite: EE 340 or any equivalent or higher-level courses. Basic understanding of electromagnetic theory and optics is required. 

Texts /References:

    1. Plasmonics: Fundamentals and Applications, S. Maier, Springer (2007) 
    2. Active Plasmonics and Tuneable Plasmonic Metamaterials, A. V. Zayats and S. Maier, Wiley (2013) 
    3. Plasmonics: Theory and Applications, T. V. Shahbazyan amd M. I. Stockman, Vol. 15. Springer Science & Business Media (2014)  
    4. Principles of Nano-Optics, L. Novotny and B. Hecht, Cambridge (2012)  
    5. Photonic Crystals:  Molding the flow of light, J.D. Joannopoulos, S. G. Johnson, J. N. Winn, and R. D. Meade, Princeton University Press (2011).  
    6. Optical Metamaterials: Fundamentals and Applications, W. Cai and V. Shalaev Springer (2010) 
    7. Tutorials in Metamaterials, M. A. Noginov and V. A. Podolskiy, CRC press (2012) 

EE 645 Numerical Methods in Electromagnetism 3-0-0-6

Course Contents:

Fundamental Concepts: Review of Electromagnetic Theory, Classification of EMProblems, Analytical solution methods for EM problems; Finite Difference Methods:Finite differencing of partial differential equations (PDEs), Applications in Guidedstructures and Wave scattering problems, Numerical Integration;

VariationalMethods: Calculus of Variations, Weighted Residual Method, Eigenvalue Problem;Method of Moments: Integral equations, Green’s Equation, Application to QuasiStatic, Scattering, Radiation and EM absorption problems; Finite Element Methods: Solution of Laplace’s equation, Solution of Poisson’s Equation, Mesh generation in 2D and 3D, Application to Electric Machines and Actuators; Transmission- line-Matrix Method: Transmission line equations, Solution to Diffusion and Wave equations; Boundary Element Methods: 2D Laplace’s and Helmholtz’s equations, 2D Diffusion equation, Green’s Functions for Potential Problem; Finite Difference Time Domain Method (FTDT): The FTDT grid and the Yee Algorithm, Numerical Stability of FDTD, Absorbing and perfectly matched layers.


    1. M. N.O. Sadiku, Numerical Techniques in Electromagnetism, CRC Press, 2nd Edn., 2001
    2. A. F. Peterson, S. L. Ray, and R. Mittra, Computational Methods for electromagnetic, Wiley IEEE Press, 1997.


    1. A R. F. Harrington, Field computation by moment methods, Wiely-IEEE Press , 1993.
    2. W. C. Gibson, The Method of Moments in Electromagnetics, Taylor & Francis, 2008.
    3. A. Taflove and S. C. Hagness, Computational Electromagnetics: The Finite Difference Time Domain Method, 3rd Edn.,Artech House, 2005.
    4. J. Jin, The Finite Element Method in Electromagnetics, 2nd Edn., John Wiley & Sons, 2002.

EE 646 Optical Measurement Techniques and Applications 3-0-0-6

Course Content:
Fundamentals of Optics: Complex representation of waves, Scalar diffraction theory, Fresnel and Fraunhofer diffraction, Frequency analysis of optical imaging systems, Optical transfer function; Light Sources and detectors: Sources of light, Fundamentals and applications of lasers, Types of laser sources, Photodetectors, CCD and CMOS image sensors, Spatial light modulator; Interferometric Optical measurement techniques and applications: Fundamentals of interferometry, Type of interferometry setups, Digital Holography, Holographic interferometry, Electronic speckle pattern interferometry, Moiré interferometry, Photoelasticity, Fringe projection profilometry; Optical coherence Tomography, Applications; Interferometric Optical measurement techniques – Data analysis: Phase shifting interferometry: Synchronous and Asynchronous, Fourier transform interferometry; Spatial and temporal fringe analysis: Single or multiple phase estimation, Single or multiple phase derivative estimation, Exponential phase signal analysis, Closed fringe analysis, Fringe denoising algorithms, Phase quality maps, Phase unwrapping algorithms, Multicomponent optical signal separation algorithms; Non-Interferometric Optical measurement techniques, analysis and applications: Digital image correlation, Brief discussion on Microscopy and Spectroscopy, Applications.

Texts/ References:

  1. J. Goodman, Introduction to Fourier Optics, W. H. Freeman, 2017.
  2. T. Yoshikawa, Handbook of Optical Metrology: Principles and Applications, CRC press, 2017.
  3. R. Sirohi, Introduction to Optical Metrology, CRC press, 2015.
  4. M. Servin, J.A. Quiroga and M. Padilla, Fringe Pattern Analysis for Optical Metrology: Theory, Algorithms, and Applications, Wiley WCH, 2014.

EE 651 Multivariable Control Theory 3-0-0-6

Course contents:

Mathematical Fundamentals: Invariant subspaces, Similarity transformations, Quotienting and equivalence classes; Canonical Representations and Feedback Laws:, Multivariable Observer and controller canonical representations, multivariable pole placement problem, multivariable observer design problem; System decomposition: Controllability indices and system invariants, Controllability subspaces and Observability subspaces, stabilizability and detectability, Disturbance decoupling and Output stabilization problems; Binary Systems:Introduction to linear modular systems.

Texts/ References:

    1. C. T. Chen, Linear System Theory and Design , 3 rd Edn., Oxford 1999.
    2. O. Gasparyan, Linear and Nonlinear Multivariable Feedback Control: A Classical Approach , John Wiley and Sons, 2007.
    3. W. M. Wonham, Linear Multivariable Control: A Geometric Approach , Springer, 1985.

EE 653 Modeling and Simulation of Dynamic Systems 3-0-0-6

Course Content:

Dynamic systems, Types of dynamic models, Frequency domain based modelling, Time domain based modelling, State space modelling of discrete time systems, Modelling examples of various practical systems. Simulation diagrams of state space models, Simulation of dynamic systems using MATLAB SIMULINK toolboxes.


  1. N. S. Nise, Control Systems Engineering, John Wiley & Sons, 2008.
  2. A. Johnson and H. Moradi, New Identifications and Design Methods, Springer-Verlag, 2005.
  3. S.Majhi, Advanced Control Theory-Relay Feedback Approach, Cengage Asia/India Pvt.Ltd, 2009.

EE 654 Nonlinear Systems and Control 3-0-0-6

Course Contents

Introduction: state-space representation of dynamic al systems, phase-portraits of second order systems, types of equilibrium points: stable/unstable node, stable/unstable focus, saddle; Existence and uniqueness of solutions: Lipschitz continuity, Picard's iteration method, proof of existence and uniqueness theorem, continuous dependence of solutions on initial conditions; Features of nonlinear dynamical systems: multiple disjoint equilibrium points, limit cycles, Bendixson criterion, Poincare-Bendixson criterion; Linearization: linearization around an equilibrium point, validity of linearization: hyperbolic equilibrium points, linearization around a solution; Stability analysis: Lyapunovstability of autonomous systems,Lyapunov theorem of stability, converse theorems of Lyapunov theorem, construction ofLyapunov functions: Krasovskii method and variable gradient method, LaSalle invariance principle, region of attraction, input/output stability of non-autonomous systems, L-stability; Control of nonlinear systems:describing functions method, passivity theorem, small gain theorem, Kalman-Yakubovich-Popov lemma, Aizermann conjecture, circle/Popov criteria, methods of integ ral quadratic constraints and quadratic differential forms for designing stabiliz ing linear controllers, multiplier techniques.

Texts/ References:

    1. H.K. Khalil, Nonlinear systems, Prentice Hall, 3rdEdn., 2002.
    2. M. Vidyasagar, Nonlinear systems analysis, 2ndEdn., Society of Industrial and Applied Mathematics, 2002.
    3. H. Marquez, Nonlinear Control Systems: Analysis and Design, Wiley, 2003.
    4. A. Isidori, Nonlinear Control Systems, Springer, 3rdEdn., 1995.
    5. F. Verhulst, Nonlinear Diffrential Equations and Dynamical Systems, Springer, 1990.

EE 655 Mathematical techniques for Control and Signal Processing 3-0-0-6

Course contents:

Basics of analysis, Banach and Hilbert spaces, standard function spaces:L2 and Hardy spaces, operator theory, approximation and projections, well-posedness and introduction to inverse problems, applications in control and signal processing. Introduction to group theory with applications in image processing.

Texts/ References:

1. Wynn C. Stirling, Todd K. Moon, Mathematical Methods and Algorithms for Signal Processing, Prentice Hall, 2000.
2. Steven B. Damelin, Willard Miller Jr, The Mathematics of Signal Processing, Cambridge University Press, 2012.
3. Alex Poznyak, Advanced Mathematical Tools for Control Engineers: Volume 1: Deterministic Systems, Elsevier, 2010.
4. Erwin Kreyszig, Introductory Functional Analysis with Applications, John Wiley & Sons, 2007.
5. I. N. Herstein, Topics in Algebra, John Wiley & Sons, 2006.

EE 656 Robust Control 3-0-0-6

Course Content:

Preliminaries:- Norms: vector, matrix, signals and systems; Linear systems: controllability and stabilizability, observability and detectability, poles and zeros of transfer function matrix, LMI.
Feedback interconnection & stability:- Well-posedness; Internal stability; Coprime factorization and stabilizing controllers.
Model uncertainty and robustness:- Model uncertainity, Small gain theorem, Kharitonov’s result; Linear fractional transformation LFT.
H2 and Hinf control:- H2 and Hinf control problems and solutions.



  1. Essentials of Robust control - Kemin Zhou with John C. Doyle, Prentice Hall, 1999.
  2. A Course in Robust Control Theory: A Convex Approach - Geir. E. Dullerud and Fernando G. Paganini, New York: Springer-Verlag, 1999.

EE 657 Intelligent Sensor and Actuator 3-0-0-6

Course Content:

Control Instrumentation and design, Component interconnection and signal conditioning, Performance and specification analysis, Classification of sensors and actuators, Theory and Analysis of Magnetic Sensors, Solid state sensors and their analysis, Linear Actuators, Fast acting actuators, Latching linear actuators, Stepper motors as actuators, Rotary sensors and actuators, Special magnetic devices, Digital Transducers


    1. Andrzei M. Pawlak, Sensors nd actuators in Mechatronics: Design and Application, CRC Press, 1st Edition 2006.
    2. Clarence W. de Silva, Sensors and Actuators: Control System Instrumentation, CRC Press, 1st Edition, 2007.

EE 659 Fuzzy Logic and Neural Networks 3-0-0-6

Course Contents:

Introduction to Fuzzy sets: Fuzzy relation, Approximate reasoning, Rules; Fuzzy control design parameters: Rule base, data base; Choice of fuzzification procedure; Choice of defuzzification procedure; Nonlinear fuzzy control; Adaptive fuzzy control; Introduction to Neural Networks: Biological Neurons, Artificial Neurons – various models, Artificial Neural Networks – various structures, Learning Strategies, Applications.

Texts / References:

  1. S. Haykin, Neural Networks: A Comprehensive Foundation, Prentice- Hall India, 2nd Edition, 1999.
  2. J. S. R. Jang, C. T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, 2nd Edition, Pearson Education, 2005.
  3. J. A. Freeman and D. M. Skapura, Neural Networks: Algorithms, Applications, and Programming Techniques, 1st Edition, Pearson Education, 2007.

EE 660 Modeling and Control of Power Electronic Converters 3-0-0-6
  • Overview of basic and advanced Power electronic converters, various applications, basics of utility power conversion, isolated and non-isolated converter circuits, types of power converter models.
  • Steady state converter analysis, Steady state modeling of the power converters, DC transformer model, loss modeling.
  • Dynamic modeling of the power converters, AC modeling of converters, state-space averaging, Transfer functions and frequency domain analysis, Extra Element Theorem.
  • Pulse Width Modulation (PWM) control of power converters, voltage source and current source inverters, 
  • Feedback control design, voltage mode and current mode control, control of inverters and rectifiers
  • Analog and digital implementation of the controllers, Advanced analysis and control techniques applied to power electronics converters.


  1. R. W. Erickson, D. Maksimovic, Fundamentals of Power Electronics, Kluwer Academic Publishers, 2004.
  2. I. Batarseh, Power Electronic Circuits, Wiley, 2004.
  3. J. Kassakian, M. F. Schlecht, and G. C. Verghese, Principles of Power Electronics, Addison-Wesley Publishing Company, 1991.

EE 661 Power Electronics for Renewable Energy Systems 3-0-0-6

Course contents:

Introduction: Potential of renewable energies in India’s future Power generation, Need of power electronics for power generation from renewable energies.
Solar PV Systems: Solar PV characteristics, Grid requirement for PV, Power electronic converters used for solar PV, Control techniques, MPPT, Grid connected and Islanding mode, Grid synchronization, PLLs, battery charging in PV systems.
Wind Energy Conversion: Wind Turbine characteristics, Grid requirement for Wind, PMSM and DFIG for wind generators, Power electronic converters for PMSM and DFIG, Control techniques, MPPT, Grid connected and Islanding mode.
Other renewable energy systems: Fuel Cells, Biogas, Biomass etc
Power electronic converters and control for Microgrids and Smart grids

Texts/ References:

1) Remus Teodorescu, Marco Liserre, Pedro Rodriguez, “Grid Converters for Photovoltaic and Wind Power Systems” Wiley-IEEE Press, January 2011.
2) Suleiman M. Sharkh, Mohammad A. Abu-Sara, Georgios I. Orfanoudakis, Babar Hussain, “Power Electronic Converters for Microgrids” Wiley-IEEE Press, April 2014.
3) Fang Lin Luo, Hong Ye, “Advanced DC/AC Inverters: Applications in Renewable Energy” CRC Press.
4) Sudipta Chakraborty, Marcelo G. Simões, William E. Kramer, “Power Electronics for Renewable and Distributed Energy Systems” Springer 2013.

EE 662 Power Electronics Applications in Power Systems 3-0-0-6
  • Power electronic converters, Basic power system operation, Role of power electronics in power systems.
  • High Voltage DC Transmission and Flexible AC Transmission Systems (FACTs), Principles of series and shunt compensators, Various FACTs devices.
  • Power Quality Requirements, types of loads, harmonics, Active and Passive filters, Shunt, series and hybrid filters, Power Quality Conditioners.
  • Uninterruptible Power Supplies, Power electronics in domestic and industrial loads
  • Power conditioning units for renewable power generation and distributed generation systems.


  1. N. G. Hingorani, L. Gyugyi, Understaning FACTS: Concepts and Technology of Flexible AC Transmission Systems, Wiley, 2000.
  2. A. Ghosh, G. Ledwich, Power Quality Enhancement Using Custom Power Devices, Springer, 2012.
  3. K. R. Padiyar, HVDC Power Transmission System, New Academic Science Ltd, 2011.
  4. R. Teodorescu, M. Liserre, P. Rodríguez, Grid Converters for Photovoltaic and Wind Power Systems, Wiley, 2013.

EE 663 Design and Realization of Power Converters 3-0-0-6

Course contents:

Ratings and Specifications of power semiconductor devices, Gate drive circuits, protection circuits, snubbers, design of power electronic circuit, different sections of power converters, types of grounds, selection of components, multi-layer printed-circuit-boards(PCB) , power PCB, issue of signal integrity, PCB design, harness design, bus bar structure, electromagnetic interference(EMI), conducted and radiated EMI, EMI filters, enclosure design, design of magnetics, thermal calculations, cooling methods, power line AC filter design, packaging of power converter, art in power electronic product design.

Texts/ References:

1. N. Mohan, Power Electronics- Converters, Applications and Design, 3rd Ed., John Wiley & Sons, 2003.
2. Abraham I. Pressman, Keith Billings, Switching Power Supply Design, 3rd Ed., McGraw-Hill, 2009.
3. Henry W Ott, Electromagnetic Compatibility Engineering, John Wiley & Sons, 2009.
4. François Costa, Eric Laboure, Bertrand Revol, Electromagnetic Compatibility in Power Electronics, Wiley, 2014.
5. Mark I. Montrose, EMC and the Printed Circuit Board: Design, Theory, and Layout Made Simple, Wiley-IEEE Press, 1998.
6. Keith Billings and Taylor Morey, Switchmode Power Supply Handbook, 3rd Ed., McGraw-Hill, 2011.

Requisite Software:
LTSpice, Design Spark PCB, Design Spark Mechanical (All are opensource.)

EE 671 Insulation and High Voltage Engineering 3-0-0-6

Course Contents:

Introduction to HV engineering course and challenges & opportunities in electric power equipment industry; Insulation engineering: Insulation materials, Stresses on power apparatus insulation & insulation systems of various power apparatus; Fundamentals of Insulation Breakdown: Electrical breakdown in gases, liquid and solid dielectrics; Stress Control: Principles of stress control, Stress distribution in multiple dielectrics, Stress calculation; Generation of high voltages in laboratory: Generation of High voltage AC by cascading and series resonant system, High DC voltages, Multistage impulse generator circuits, Impulse current generator; Measurement of High Voltages : AC voltage, DC voltage, Impulse voltages; Non-Destructive Insulation Assessment: Schering bridge, Ampere turns bridge, Standard Capacitor, Partial discharge; Testing of Power apparatus: Non-destructive tests to check integrity of insulation of on various power apparatus, Impulse test of transformers.

Texts / References:

  1. E. Kuffel, W. S. Zaengl and J. Kuffel, High Voltage Engineering Fundamentals, Butterworth-Heineman Press, Oxford, 2000.
  2. M S Naidu and V Kamaraju, High Voltage Engineering, Tata McGraw Hill, 2004
  3. E. Naser, Fundamentals and Gaseous Ionization and Plasma Electronics, John Wiley & Sons, Inc., New York, 1971.
  4. L. L. Alston, High Voltage Technology, Oxford University Press, 1968.
  5. A. V. Hippel and A. S. Labounsky, Dielectric Materials and Applications, Artech House, Boston, 1995.

EE 672 Electrical Power Quality and Reliability 3-0-0-6

Course Contents

Conventional power definitions and limitations; Evaluation of modern power theories; Power components in single phase and three phase power circuits based on conventional and modern power theories; Power quality (PQ) in power system: definitions, identification and classification; Overview of classical PQ improvement schemes; Introduction of custom power devices (CPD); Operation and control of distribution static compensator (DSTATCOM) for load compensation and voltage regulation; Series compensation with dynamic voltage restorer (DVR); Unified power quality conditioner (UPQC) for shunt and series compensation; Hybrid custom power devices.

Texts / References:
[1]. Hirofumi Akagi, Edson Hirokazu Watanabe and Mauricio Aredes, “Instantaneous power theory and applications to power conditioning”, John Wiley & Sons, 2007.
[2]. Arindam Ghosh and Gerard Ledwich, “Power quality enhancement using custom power devices”, Springer Science & Business Media, 2012.
[3]. Narain G Hingorani and Laszlo Gyugyi, “Understanding FACTS: concepts and technology of flexible AC transmission systems,” Wiley-IEEE press, 2000.
[4]. Mahesh Kumar, "NPTEL Course on Power Quality in Power Distribution Systems”, web link .

EE 673 Operation and Planning of Power Distribution Systems 3-0-0-6

Course Contents:

Primary and secondary distribution system layouts: introduction, substation layout, substation location, construction, and bus schemes, the rating of distribution substation, overhead and underground distribution networks, distribution line construction, distribution system line conductors; Reliability assessment of distribution systems: introduction, reliability modelling concept, different reliability indices, customer interruption cost evolution and customer damage function; Distribution system planning: introduction, different components of distribution system planning, different planning approaches, planning models and solution strategies; Distribution system automation and smart grid: introduction to distribution system automation, the basic elements of distribution system automation, power market deregulation and distribution system automation, load management at different peak and off-peak duration, compatibility of load management with system design and operation, smart grid and smart metering; Integration of Distributed Generation (DG): introduction to DG, Effect of renewable energy sources on power distribution systems.

[1] T. Gonen. Electric Power Distribution System Engineering; CRC Press, 3rd Edition, 2014.
[2] H. Lee. Willis. Power Distribution Planning Reference Book; CRC press; 2nd Edition, Revised and Expanded, 2004.
[3] A. S. Pabla, Electric Power Distribution; Tata Mcgraw-Hill Publishing Company Ltd., 5th Edition, 2007.
[4] Math Bollen and Fainan Hassan, Integration of Distributed Generation in the Power System; IEEE Press, 2011.
[5] R. Billington and R. Allan, Reliability Evaluation of Power Systems; Springer, Berlin, 2nd Edition, 1996.

EE 674 Synchrophasor Technology 3-0-0-6

Course Contents:

Introduction to Synchrophasor technology: basic architecture and communication requirement; Phasor and frequency estimation; Basic principles for Wide area monitoring and control in real-time; Dynamic modeling of synchronous generator; Transient stability monitoring and control; Small signal monitoring and control; Wide area power system stabilizers; Synchrophasor applications in power system protection and emergency control; Optimal placement of phasor measurement units; State estimation; Real-time monitoring and control of voltage stability.


    1. A. G. Phadke and J. S. Thorp, Synchronized Phasor Measurements and their Applications, Springer, 2008.
    2. M. Shadidehpour and Y. Wang, Communication and Control in Electric Power System, Wiley, 2003.


    1. P. Kundur, Power System Stability and Control, McGraw-Hill, 1995.
    2. P. M. Anderson and A. A. Fouad, Power System Control and Stability, 2nd Edition, Wiley, 2003.
    3. Hsiao – Dong Chiang, Direct Methods for Stability Analysis of Electric Power Systems: Theoretical Foundation, BCU Methodologies, and Applications, Wiley, 2011.

EE 675 High Voltage Transmission 3-0-0-6

Overview: Comparison of EHV AC and DC transmission, description of DC transmission systems, modern trends in AC and DC transmission, Corona and corona loss in transmission lines. EHV AC Systems: Limitations of extra long AC transmission, Voltage profile and voltage gradient of conductor, Electrostatic field of transmission line, Reactive Power planning and control, traveling and standing waves, EHV cable transmission system. Static Var System: Reactive VAR requirements, Static VAR systems, SVC in power systems, design concepts and analysis for system dynamic performance.

HVDC System: Converter configurations and their characteristics, DC link control, converter control characteristics; Monopolar operation, converter with and without overlap, smoothing reactors, transients in DC line, converter faults and protection, HVDC Breakers.

Power flow analysis in AC/DC systems: Component models, solution of DC load flow, per unit system for DC quantities, solution techniques of AC-DC power flow equations, Parallel operation of HVDC/AC systems.


    1. Begamudre R.D., EHV AC Transmission Engineering, 2nd Edn., Wiley Eastern Ltd., New Delhi, 1991.
    2. Arrillaga J., HVDC Transmission, IEE Press, London, 1983.


    1. Kimbark E., Direct Current Transmission, Vol-I, John-Wiley & Sons, N.Y., 1971.
    2. Padiyar K.R., HVDC Power Transmission Systems, Wiley Eastern Ltd., New Delhi,1990.
    3. Arrillaga J. and Smith B.C., AC-DC Power System Analysis, IEE Press, London,1998.
    4. Hingorani N.G. and Gyugyi L., Understanding Facts, IEEE Press, New York,1999.

EE 680 Electric and Hybrid vehicles 3-0-0-6

Course Content

Introduction to Hybrid Electric Vehicles, Conventional Vehicles: Basics of vehicle performance, vehicle power source characterization, transmission characteristics, mathematical models to describe vehicle performance, Hybrid Electric Drive-trains, Electric Drive-trains, Electric Propulsion unit Energy Storage Requirements in Hybrid and Electric Vehicles, Hybridization of different energy storage devices, Sizing the drive system, Energy Management Strategies, Implementation issues of energy management strategies, Case Studies: Design of a Hybrid Electric Vehicle (HEV), Design of a Battery Electric Vehicle (BEV).


    1. Lino Guzzella and Antonio Sciarretta, Modern Electric, Hybrid Electric and Fuel Cell Vehicles: Fundamentals, Theory and Design, CRC Press, 2nd Edition, 2009
    2. James Larminie and John Lowry, Electric Vehicle Technology Explained, Wiley, 1st Edition, 2003
    3. Lino Guzella, Antonio Sciarretta, Vehicle Propulsion Systems: Introduction to Modeling and Optimization, Springer, 2nd Edition, 2007.

EE 681 Advanced Electrical Drives 3-0-0-6

Course Content

Motors with continuous rotation, Electromagnetic Stepping Drives, Drives with limited motion, Piezoelectric drives, Open loop and closed loop control of fractional horse power motors, Magnetic bearings and their control, Integration and Control of Mechanical transfer units such as gears, pulleys, flexible drives etc., Project design of drive systems, Application of Artificial Intelligence in Electric Drives, AI based steady state and transient analysis of Induction Machines, AI based Switch Reluctance Machine performance estimation and Control.


    1. Hans Dieter Stoelting, Handbook of fractional Horsepower Drives, Springer, 1st edition, 2009
    2. Ion Boldea, Syed A. Nasar, Electric Drives, CRC Press, 2nd Edition, 2005
    3. Peter Vas, Artificial Intelligence Based Electrical Machines and Drives: Application of Fuzzy, Neural and Genetic Algorithm Based Techniques, Oxford University Press, 1999.


Course Contents:

Reference Frame: Commonly used reference frames, Transformation between reference frames; Transformations in Machines: Power invariance, 3-phase to 2-phase transformation, Park’s Transformation; DC Machines: Voltage and torque equations, transfer function of DC Machines, Steady State Analysis of DC Machines; Polyphase Induction Machines: D-Q model, axes transformation, Steady state analysis from different frames of references; Polyphase Synchronous Machines: Equivalent circuit, Park’s Model, Shot Circuit Analysis, Steady State Analysis; Permanent Magnet Machines: Basic operation principle, Park’s model, Steady State analysis for various PWM techniques.


  1. A. K. Mukhopadhyay, Matrix Analysis of Electrical Machines, New Age, 1996.
  2. P. Vas, Electrical Machines and Drives: A Space-Vector Theory Approach (Monographs in Electrical and Electronic Engineering), Oxford University Press, 1993.


  1. D. O'Kelly and S. Simmons, Introduction to Generalized Electrical Machine Theory, McGraw- Hill Education, 1968.

EE 692 Detection and Estimation Theory 3-0-0-6

Course Contents:

Review of random process, problem formulation and objective of signal detection and signal parameter estimation; Hypothesis testing: Neyman-Pearson, minimax, and Bayesian detection criteria; Randomized decision; Compound hypothesis testing; Locally and universally most powerful tests, generalized likelihood-ratio test; Chernoff bound, asymptotic relative efficiency; Sequential detection; Nonparametric detection, sign test, rank test. Parameter estimation: sufficient statistics, minimum statistics, complete statistics; Minimum variance unbiased estimation, Fisher information matrix, Cramer-Rao bound, Bhattacharya bound; Linear models; Best linear unbiased estimation; Maximum likelihood estimation, invariance principle; Estimation efficiency; Least squares, weighted least squares; Bayesian estimation: philosophy, nuisance parameters, risk functions, minimum mean square error estimation, maximum a posteriori estimation.

Texts / References:

  1. H. V. Poor, An Introduction to Signal Detection and Estimation, 2nd edition, Springer, 1994.
  2. S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory, Prentice Hall PTR, 1998.
  3. S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Prentice Hall PTR, 1993.
  4. H. L. Van Trees, Detection, Estimation and Modulation Theory, Part I, John Wiley, 1968.
  5. D. L. Melsa and J. L. Cohn, Detection and Estimation Theory, McGraw Hill, 1978.
  6. L. L. Scharf, Statistical Signal Processing: Detection, Estimation, and Time Series Analysis, Addison-Wesley, 1990.
  7. V. K. Rohatgi and A. K. M. E. Saleh, An Introduction to Probability and Statistics, 2nd edition, Wiley, 2000.

EE 693 Advanced Topics in Random Processes 3-0-0-6

Course Contents

Convergence of a sequence of random variables; Chernoff bound and large deviations theory; mean-square calculus- stochastic continuity derivatives and integrals; ergodicity; KarhunenLoeve expansion; Random walk process; Discrete time Markov chains: recurrence analysis, Foster's theorem; continuous time Markov Process; Poisson and birth and death processes; Wiener process and Brownian motion process.


    1. D. R. Cox, D. R. and H.D. Miller, The Theory of Stochastic Processes, Chapman & Hall - CRC, 177.
    2. H. Stark and J. W. Woods, Probability and Random Processes with Application to Signal Processing, 3/e, Pearson Education, 2002
    3. B. Hajek, An Exploration of Random Processes for Engineers, Course Notes, 2005,

EE 694 Introduction to Parallel Computing 3-0-0-6

Course Content:
Scope of Parallel Computing: Limits to parallelizability, NC-reductions, P-completeness; Parallel programming platforms; Introduction to high performance computing and parallel programming: shared memory parallel programming, distributed parallel programming, data parallel and task parallel models, parallel programming patterns, Amdahl's Law; Parallel algorithm design: decomposition, task and interactions; Communication models: synchronous and asynchronous; analytical modeling of parallel programs; Programming using message passing paradigm and shared address space: Threads, OpenMP, Intel TBB, MPI, CUDA, Hybrid parallel programming by combining pThreads and MPI calls; Case studies: Image processing, analog/digital circuit simulation, smart grid;

1. A. Grama, G. Karypis, V. Kumar, A. Gupta, “Introduction to parallel computing”, 2nd Edition, Addison-Wesley, 2004.
2. Joseph Ja'Ja', “An introduction to parallel algorithms”, 1st Edition, Addison-Wesley, 1992

1. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, “Introduction to Algorithms”, 3rd Edition, PHI Learning, 2010.
2. Frank Thomson Leighton, “Introduction to Parallel Algorithms and Architectures: Arrays, Trees and Hypercubes”, 1st Edition, Morgan Kaufmann Publishers, 1991.
3. Michael T. Heath, Abhiram Ranade, Robert S. Schreiber, “Algorithms for Parallel Processing”, 1st Edition, Springer, 1998.
4. Karl Heinz Hoffmann, A. Meyer, “Parallel Algorithms and Cluster Computing: Implementations, Algorithms and Applications”, Illustrated Edition, Springer, 2006.
5. Kontoghiorghes E. J., “Parallel Algorithms for Linear Models: Numerical Methods and Estimation Problems”, Springer, 2000.
6. Henri Casanova, Arnaud Legrand, Yves Robert, “Parallel Algorithms”, Taylor & Francis/BSP Books, 2008.
7. Jacques M. Bahi, Sylvain Contassot-vivier, Raphael Couturier, “Parallel Iterative Algorithms: From Sequential to Grid Computing”, Chapman & Hall/crc, 2007

EE 695 Data-Driven System Theory 3-0-0-6

Course Content:

Quick review of Dynamical system properties and matrix theory, bifurcation and Chaotic systems, Non-linear time series analysis, review of machine learning methods, data-driven modeling and dynamical systems (dynamic mode decomposition, Koopman operators, ODE, PDE), Construction of dynamical equation from time series data, State space reconstruction by machine learning methods, examples from model reduction (ODE, PDE), chaotic time series analysis.


1. Brunton, S. L., Kutz, J. N., Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control, First Edition, Cambridge University Press, 2019.
2. Carlo Novara, Simone Formentin, Data-Driven Modeling, Filtering and Control: Methods and Applications, First Edition, Institution of Engineering and Technology, 2019.
3. Strogatz, S. H., Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, First Edition, Perseus Books Publishing, 1994.
4. Kutz, J. N., Brunton, B. W., Proctor, J. L., Brunton, S. L., Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, First Edition,  Society for Industrial and Applied Mathematics, 2016
5. Strang, G., Linear Algebra and Learning from Data, First Edition, Wellesley-Cambridge Press, 2019.

EE 720 Sparse Representation and Compressive Sensing: Theory Applications 3-0-0-6

Course contents:

Introduction to signal representations: Fourier transform, band limited signals, sampling bandlimited signals; Sparse representation of signals: wavelet transform, ridgelet transform,curvelet transform; Sampling sparse signals (compressive sensing): incoherence, restrictedisometry property, null space property, random matrices; Robust and stable reconstruction:L1 minimization, basis pursuit, matching pursuit; Applications of sparse representations:denoising, compression, dictionary design; Applications of Compressive Sensing: analog-todigitalconversion, imaging, radar, DNA microarray, channel estimation; Extensions: low- rankmatrices, matrix completion, nuclear-norm minimization.


    1. M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, Springer, 2010.
    2. J. L. Starck, F. Murtagh and J. M. Fadili, Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity, CUP, 2010.


    1. G. Strang, Linear Algebra and Its Applications, 4th Ed., Cengage, 2006.
    2. G. Grimmett and D. Stirzaker, Probability and Random Processes, OUP, 2001.
    3. S. Boyd and L. Vandenberghe, Convex Optimization, CUP, 2004.

EE 721 Advanced Topics in Signal Processing 3-0-0-6

Course Contents:

Multirate signal processing: Fundamentals of multirate systems: Introduction, basicmultirate operations,Interconnection of building blocks, Polyphase representation,Multistage implementations, Special filters and filter banks; Maximally decimated filterbanks: Introduction, Errors created in QMF bank, Alias free QMF system, Powersymmetric QMF banks, M-channel filter banks, Polyphase representation, Perfect reconstruction systems;

Paraunitary Perfect Reconstruction (PR) Filter Banks: Introduction, Lossless transfer matrices, Filter bank properties induced byparaunitariness, Two channel FIR paraunitary QMF banks, Two channel paraunitaryQMF lattice, M-channel FIR paraunitary filter banks;

Linear Phase Perfect Reconstruction QMF Banks: Introduction, Lattice structures for linear phase FIR PR QMF banks, Formal synthesis of linear phase FIR PR QMF lattice;

Cosinemodulated Filter Banks: Introduction, Pseudo QMF bank, Design of pseudo QMFbank, Efficient polyphase structures, Cosine modulated perfect reconstructionsystems;

Applications of Multirate Signal Processing: Analysis of audio, Speech,Image and video signals;

Time frequency signal analysis and processing: Time-Frequency concepts, Time-domain representation, Frequency domain representation,Joint time-frequency representation, Desirable characteristics of a time-frequency distribution (TFD), Analytic signals, Hilbert transform, Duration, Bandwidth, Bandwidthduration product, Uncertainty principle, Instantaneous frequency, Time delay;

Time-Frequency Distributions: Wigner distribution, Wigner-ville distribution, Time-varying power spectral density, Short-term Fourier transform, Spectrogram, Gabor transform,Instantaneous power spectra, Energy density, Quadratic TFDs, Relationship betweenTFDs;

Applications of Time-Frequency Analysis: Analysis of non-stationary signalslike speech, audio, image and video signals.


    1. P. P. Vaidyanathan, Multirate Systems and Filter Banks, Pearson-Education, Delhi, 2004.
    2. B. Boashash, Time-Frequency Signal Analysis and Processing: A Comprehensive Reference, Elsevier, UK, 2003.
    3. L. Cohen, Time-Frequency Analysis, Prentice Hall, 1995.
    4. F. Hlawatsch and F. Auger, Time-Frequency analysis: Concepts and Methods, Wiley-Iste, 2008
    5. A. Spanias, T. Painter and V. Atti, Audio Signal Processing & Coding, Wiley-Interscience, NJ, USA, 2007.

EE 722 Video Analytics 3-0-0-6

Course Contents:

Introduction to Video Analytics; Ontologies in Computer Vision; Recognition Problems in Computer Vision; Surveillance Video Analytics – System Architecture, Ontologies, Research Issues and Information Visualization; Background Modeling for Static and Pan-Tilt Cameras; Object Detection - Features, Bag of Words Formulation, Dictionary based Approaches, CNN based Methods; Human detection and localization; Object Tracking - Particle Filter, Kernel based Tracker, L1 Tracker, Discriminative Model based techniques, Multiple Object Tracking, Activity Recognition – Human Action Recognition, Scene Activity Identification; Surveillance Analytics; Television News Broadcast Video Analytics - System Architecture, Ontologies, Research Issues and Query Response Visualization; Text Detection and Recognition; Face Detection, Tracking, Linking and Recognition; Broadcast Segmentation - shot, scene and story segmentation; Features and Algorithms for Video Event Discovery; Broadcast Analytics; Research Directions in Video Analytics..


1. Milan Sonka, Vaclav Hlavac and Roger Boyle, "Image Processing, Analysis and Machine Vision", Cengage, Third Edition (2013).
2. Ian H. Witten, Eibe Frank and Mark A. Hall, "Data Mining: Practical Machine Learning Tools and Techniques", Elsevier; Third edition (2010).
3. Santanu Chaudhury, Anupama Mallik and Hiranmay Ghosh, "Multimedia Ontology: Representation and Applications", Chapman and Hall/CRC; First Edition (2015).
4. Ian Goodfellow, Yoshua Bengio and Aaron Courville, "Deep Learning", MIT Press (2017) .
5. Abdessalan Bouzerdoum, George Mamic and M. Bennamoun, "Object Recognition: Fundamentals & Case Studies", Universities Press, First Edition (2008).
6. Xiaogang Wang, "Deep Learning in Object Recognition, Detection, and Segmentation", Foundations and Trends in Signal Processing: Vol. 8: No. 4, pp 217-382, 2016.
7. Rama Chellappa, Aswin C. Sankaranarayanan, Ashok Veeraraghavan and Pavan Turaga, "Statistical Methods and Models for Video-Based Tracking, Modeling, and Recognition", Foundations and Trends in Signal Processing: Vol. 3: No. 1–2, pp 1-151, 2010.
8. Phuong Vo.T.H, Martin Czygan, Ashish Kumar and Kirthi Raman, "Python: Data Analytics and Visualization", Packt Publishing Limited (2017)

EE 647 Microsensors and Nanosensors 3-0-0-6

Course Content:
Introduction:Classification of Sensors, Sensor characteristics(transfer function, hysteresis, nonlinearity, uncertainty, accuracy, repeatability etc.), Principles of Sensing, Interface Electronic Circuits. Positions Sensors: Motion Sensor, Displacement sensors,Velocity and Acceleration sensors,Force & Pressure Sensors: Force, Strain and Tactile Sensor; Pressure Sensor; Flow Sensor; Acoustic Sensor;Other Electronic Sensors: Humidity Sensor; Light Sensor; Radiation Sensor; Temperature Sensor; Gas and Chemical Sensor(MOX based sensors, ChemFET, Electrochemical)


    1. V.K.Khanna, Nanosensors, 2nd Ed., CRC Press, 2021.
    2. S Nihtianov, and A. Luque, Smart Sensors and MEMS, 2nd Ed.,Springer, 2018.
    3. G. R. Sinha, Advances in Modern Sensors, 1st Ed.,IOP Publishers, 2020.
    4. J. Vetelino and A. Reghu, Introduction to Sensors, 1st Ed., CRC Press, 2011.
    5. W. Lang, Sensors and Measurement Systems, 2nd Ed., River Publishers, 2021.
    6. E.G.Bakhoum, Micro-and Nano-Scale Sensors and Transducers, 1st Ed., Taylor&Francis, 2019.

EE 648 Terahertz Electronics 3-0-0-6

Course Content:
Course Content: THz Electronics: Introduction to THz technology, applications, THz gap, interaction with matter, beam propagation; THz sources: Vacuum electron devices, lasers, novel devices; THz detectors: Thermal detectors, pyroelectric detectors, heterodyne receivers; Cutting edge THz technologies and their applications: Imaging systems, wireless communication towards 6G and beyond, bio-medical applications, spectroscopy.


    1. Jae-Sung Rieh, Introduction to Terahertz Electronics, Springer Nature, 2021.
    2. A. D. Grigorev, Terahertz Electronics, Cambridge Scholars Publishing, 2020.
    3. D. Pavlidis, Fundamentals of Terahertz Devices and Applications, John Wiley & Sons, 2021.
    4. A. Biswas et al., Emerging Trends in Terahertz Solid-State Physics and Devices: Sources, Detectors, Advanced Materials, and Light-matter Interactions, Springer Nature, 2020.
    5. T. Kürner, D. Mittleman, and T. Nagatsuma, THz Communications: Paving the Way Towards Wireless Tbps, Springer, 2022.
    6. I. Malhotra and G. Singh, Terahertz Antenna Technology for Imaging and Sensing Applications, Springer, 2021.
    7. A. Rogalski, Infrared and terahertz detectors, CRC Press, 2019.
    8. A. Banerjee, B. Chakraborty, H. Inokawa and J. N. Roy, Terahertz Biomedical and Healthcare Technologies: Materials to Devices, Elsevier, 2020.

EE 604 Applied Signal and Image Processing 3-0-0-6

Course Content:
Introduction: Applied Signal Processing, Applied Image Processing; Signal Denoising: Order Statistic Filtering, Empirical Mode Decomposition, Stationary Wavelet Transforms, Kalman Filter, Particle Filter; Signal Matching: Correlation Filters (MOSSE, ASEF), Time-series motifs, Dynamic time warping; Spectral Estimation: Yule-Walker, MUSIC Algorithm; Image Projection Functions: Integral Projection Functions, Variance Projection Functions, Hybrid Variance Projection Functions; Image Descriptors: Integral Image, Laplacian of Gaussians (LoG), Histogram of Oriented Gradients (HoG), Eigenfeatures, Local Binary Patterns; Applications: Fault Diagnosis, Face Detection, Face Recognition, Optical Character Recognition.


    1. Manolakis, Dimitris G., and Vinay K. Ingle. Applied digital signal processing: theory and practice. Cambridge university press, 2011.
    2. Misiti, Michel, et al., eds. Wavelets and their Applications. John Wiley & Sons, 2013.
    3. Chui, Charles K., and Guanrong Chen. Kalman filtering. Berlin, Germany: Springer International Publishing, 2017.
    4. Bergman, Niclas. Recursive Bayesian estimation. Department of Electrical Engineering, Linköping University, Linköping Studies in Science and Technology. Doctoral dissertation 579.11 (1999).
    5. Fan, Bin, Zhenhua Wang, and Fuchao Wu. Local image descriptor: modern approaches. Vol. 108. Springer Berlin Heidelberg, 2015.
    6. Wang, Yi-Qing. An analysis of the Viola-Jones face detection algorithm. Image Processing On Line 4 (2014): 128-148.
    7. Barnouti, Nawaf Hazim, et al. Face detection and recognition using Viola-Jones with PCA-LDA and square euclidean distance. International Journal of Advanced Computer Science and Applications (IJACSA) 7.5 (2016): 371-377.
    8. Mori, Shunji, Hirobumi Nishida, and Hiromitsu Yamada. Optical character recognition. John Wiley & Sons, Inc., 1999.

EE 601 Introduction to Distributed Control Systems 3-0-0-6

Course Content:
Preliminaries of system theory; Basics of graph theory and linear algebra; Notion of networked control systems, its utilities and differences with conventional control techniques; Modelling, stability analysis and control of networked systems; Differences between centralized and decentralized/distributed control; Concept of multi-agent systems; Distributed Cooperative control: consensus control, leader-follower control, rendezvous control, formation control of multi-agent systems; Applications to vehicle platooning and multi-robot systems.


    1. W. Ren and R. W. Beard, Distributed Consensus in Multi-vehicle Cooperative Control: Theory and Applications, 1st ed, Springer-Verlag London Ltd, 2008
    2. M. Mesbahi and M. Egerstedt, Graph Theoretic Methods in Multiagent Networks, Princeton Series in Applied Mathematics, 2010
    3. Z. Li and D. Zhiseng, Cooperative Control of Multi-Agent Systems, CRC Press, 2015.
    4. F. Lewis, H. Zhang, K. H. Movric and A. Das, Cooperative Control of Multi-Agent Systems: Optimal and Adaptive Design Approaches, Springer, 2014.

EE 602 Adaptive and Learning-based Control 3-0-0-6

Course Content:
Introduction to adaptive control systems, Parameter estimation and system identification – an overview, Lyapunov stability theory and its importance, Model reference adaptive control, Persistent excitation condition and parameter convergence, Direct and indirect adaptive control, Real-time parameter estimation, Composite adaptation, Self-tuning control, Adaptive pole placement design, Auto-tuning techniques, Robust adaptive control schemes, Adaptive control of nonlinear systems, Gain scheduling, Adaptive backstepping design, Learning based adaptive control, Direct and Indirect adaptive control using neural networks


    1. K. S. Narendra and A. M. Annaswamy, Stable Adaptive Systems, 2nd edition, Dover Publications, 2012
    2. S. Sastry and M. Bodson, Adaptive Control: Stability, Convergence and Robustness, 1st edition, Dover Publications, 2011
    3. M. Benosman, Learning-Based Adaptive Control: An Extremum Seeking Approach – Theory and Applications, 1st edition, Butterworth-Heinemann, 2016
    4. K. J. Astrom and B. Wittenmark, Adaptive Control, 2nd edition, Dover Publications, 2008
    5. P. A. Ioannou and J. Sun, Robust Adaptive Controls, 1st edition, Dover Publications, 2013
    6. M. Krstic, I. Kanellakopoulos, and P. Kokotovic, Nonlinear and Adaptive Control Design, 1st edition, Wiley-Interscience, 1995
    7. L. Behera and I. Kar, Intelligent Systems and Control, 1st edition, Oxford University Press, 2009

EE 677 Smart power grids for a sustainable future 3-0-0-6

Course Content:
Overview of electricity demand and supply; Fundamentals of energy and electric power, a survey of traditional and new energy resources; Operation and planning of power grid today and requirements for tomorrow, industry structure; Control and optimization at many scales; Electricity markets: today and tomorrow, the political economy of electricity; New challenges and opportunities for power grids: renewable and distributed energy sources, climate change, energy storage, electric vehicles; Applications enabled by data analytics and DC technologies.


    1. David MacKay, Sustainable Energy — without the hot air, UIT Cambridge Ltd., 2009, ISBN 9780954452933
    2. Allen J. Wood, Bruce F. Wollenberg and Gerald B. Sheble, Power generation operation and control, 3rd ed., John Wiley, 2014.
    3. Stuart Borlase, Smart Grids: Advanced Technologies and Solutions, 2nd ed., CRC press, 2017

EE 791 Stochastic Analysis of Wireless Networks 3-0-0-6

Course Content:
Introduction: Stochastic processes and their classifications, properties of stochastic processes, introduction to stochastic geometry-study of random spatial patterns (point processes, random tessellations etc.), spatial point process (1D and 2D), examples and types, Binomial and Poisson point processes (PPP), properties of PPP, classifications, Campbell's theorem, Probability generating functional (PGFL), Matern-Hardcore process, Palm distribution, Slivnyak Theorem, Campbell Mecke Theorem, Ad-hoc network SINR and interference analysis, Extension to multi-antenna systems, Interference distribution, and related bounds, Transmission capacity, Analysis of cellular networks (single and multi-tier), PPP-based base station distribution, Base station association, uplink and downlink performance analysis, probabilistic LoS/NLoS link modeling, Emerging wireless network examples (Ultra-dense networks, IoT, Cell-free massive MIMO, vehicular networks etc.) and performance study.


    1. M. Haenggi, Stochastic Geometry for Wireless Networks, Cambridge University Press, 2012
    2. F. Baccelli, and B. Blaszczyszyn, Stochastic Geometry and Wireless Networks: Volume 1 Theory, Foundations and Trends® in Networking, vol. 3, no. 3-4, pp. 249-449, 2010.
    3. M. Haenggi, and R.K. Ganti, Interference in Large Wireless Networks, Foundations and Trends® in Networking, vol. 3, no. 2, pp. 127-248, 2009.

EE 616 Circuits for Signal Processing 3-0-0-6

Course Content:
Sensor Signals: typical characteristics, fundamental operations required. Noise in electronic circuits and its effect on the signal processing. Different types of amplifiers: voltage, current, and charge-based topologies. Analog Filters: fundamentals, passive filters, and active filters. Data converters: principles, digital-to-analog converters, analog-to-digital converters. Case studies.


    1. R. Baker, CMOS Mixed-Signal Circuit Design, Wiley India, reprint 2008.
    2. R. Schaumann, H. Xiao, M. E. Van Valkenburg, Analog Filter Design, Ed. 2, Oxford University Press, 2010.

EE 615 Advanced Photovoltaics 3-0-0-6

Course Content:
Part 1 - Review of basics: Radiative and non-radiative recombination mechanisms, Defects, Lifetime, Transition rates, Shockley-Queisser Limit, Review of charge transport mechanisms and pn junction theory, Two-diode model; Part 2 - Device design and fabrication: Basic structures and design considerations of various types of solar cells including thin film and state-of-art novel devices; Fabrication methods and related issues; Part 3 - Efficiency enhancement techniques: Loss mechanisms and Thermal behavior, Light intensity dependence of solar cell efficiency parameters; Concepts for improving efficiency of solar cells, Up- and down conversion of photons, Hot electrons, Multijunction, Tandem, and 3D architectures; Part 4 - Advanced characterization techniques: Kelvin probe, Microwave conductivity, Quantum efficiency measurement, Luminescence analysis, and Transient analysis methods.


    1. Peter Wufrel and Uli Wufrel, Physics of Solar Cells – From Basic Principles to Advanced Concepts, 3rd Ed, Wiley, 2016.
    2. Daniel Abou-Ras, Thomas Kirchartz, and Uwe Rau, Advanced Characterization Techniques for Thin Film Solar Cells, 2nd Ed, Wiley, 2016.
    3. Olivier Dupre, Rodolphe Vailon, and Martin A. Green, Thermal Behaviour of Photovoltaic Devices – Physics and Engineering, Springer, 2017.
    4. Arthur Willoughby and Gavin J. Conibeer, Solar Cell Materials – Developing Technologies, Wiley.

EE 665 Power Electronic Systems for Electric Vehicles 3-0-0-6

Course Content:
Introduction of hybrid (HEV), plug-in hybrid (PHEV) and electric vehicles (EV) systems, Power electronic systems for electric vehicles, bidirectional ac-dc converters, bidirectional dc-ac converters, bidirectional dc-dc converters, Battery overview and battery management system, power converter system for battery charging, power converter system for motor drive, Digital control for various power converters, wireless power transfer (WPT)-inductive and capacitive.


    1. Ehsani, Mehrdad, Yimin Gao, Stefano Longo, and Kambiz M. Ebrahimi. Modern electric, hybrid electric, and fuel cell vehicles. CRC press, 2018.
    2. Mohan, Ned, Tore M. Undeland, and William P. Robbins. Power electronics: converters, applications, and design. John wiley & sons, 2003.
    3. Rim, Chun T., and Chris Mi. Wireless power transfer for electric vehicles and mobile devices. John Wiley & Sons, 2017.
    4. Kazimierczuk, Marian K. Pulse-width modulated DC-DC power converters. John Wiley & Sons, 2015.
    5. Erickson, Robert W., and Dragan Maksimovic. Fundamentals of power electronics. Springer Science & Business Media, 2007.