Course Number

EC5104

Course Credit

L-T-P-C: 3-0-2-4

Course Title

Digital VLSI System

Learning Mode

Lectures and Labs

Learning Objectives

Complies with Program Goals 1, 2 and 3

Course Description

The Digital VLSI Systems course covers the design, analysis, and implementation of Very-Large-Scale Integration (VLSI) circuits. It focuses on techniques for optimizing digital systems for performance, power, and area.

Course Outline

Digital Systems and its applications; Basics on manufacturing process of Digital systems; Device and Wire Model; Design and implementation strategies of digital VLSI systems: Full and Semi-custom; Static and Dynamic MOS Logic design and Characteristics: Combinational and sequential circuits and systems; Introduction to ASIC and FPGA based system Design; Digital System and HDL; Design Steps of digital systems; Digital Arithmetic circuits; Semiconductor Memory and peripheral circuits and Systems; Digital IC testing and validation methodologies.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. Ming-Bo Lin, “Introduction to VLSI Systems: A Logic, Circuit, and System Perspective”

Indian Edition, CRC Press, 2011.

2. Seetharaman Ramachandran, “Digital VLSI Systems design”, 1st Edition, Springer, 2007.

3. Michael John Sebastian Smith, “Application Specific Integrated Circuit” Addison Wesley,

Reprint edition, 1997.

4. J. M. Rabaey, A. Chandrakasan, and B. Nikolic, “Digital Integrated circuits: A design

perspective” 2nd Edition, Pearson Education India, 2016.

5. Sung-Mo Kang, and Yusuf Leblebici, “CMOS Digital Integrated Circuits”, 3rd Edition

McGraw-Hill Education, 2002.

6. Michael, D. Ciletti, “Advanced Digital Design with the Verilog HDL”, PHI Learning

Private Limited, 2012.

7. Samir Palnitkar, “Verilog HDL: A Guide to Digital Design and Synthesis”, Second Edition,

Prentice Hall PTR, 2003.

Course Number

EC5105

Course Credit

L-T-P-C: 3-0-2-4

Course Title

Embedded System

Learning Mode

Lectures and Labs

Learning Objectives

Complies with Program Goals 1, 2, 3 and 4

Course Description

Embedded Systems focus on the design and integration of hardware and software in specialized computing systems. The course explores real-time operating systems, microcontrollers, and applications in various domains.

Course Outline

Introduction to the Embedded systems, Basics of Microprocessors and Microcontrollers, Embedded System models and Development Cycle, Embedded system design constraints

Sensors, Actuators, Embedded processor and memory architecture, Analog to Digital (A/D) convertors, D/A convertors

Introduction to different processors, Arduino-Architecture, communication, Field Programmable Gate Array (FPGA)-configurable logic blocks, ARM Processor- Architecture, Instruction Set, Pipelining, Interfacing, Pulse Width Modulation

Communication Interfaces: Serial and Parallel communication, Onboard Communication Interfaces (UART, SPI, I2C) and External Communication Interfaces (IR, Wireless-Bluetooth, Wireless LAN, USB, Ethernet etc.),

Introduction to Embedded OS and RTOS, Task scheduling-clock-driven and event-driven, RMA and EDF scheduling, Voltage Scheduling, priority inversion, inheritance and ceiling protocol, Multi-tasking

State Charts, Finite State Machines, Hierarchical state machines, Program State Machines, Specification and description language (SDL), Embedded system analysis and verification.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. P. Marwedel: Embedded System Design, Springer, ISBN978-3-319-56045-8,2018.

2. G.C.Buttazzo:HardReal-TimeComputingSystems.SpringerVerlag,ISBN978-1-4614-0676-1,2011.

3. Peter Marwedel, “Embedded System Design: Embedded Systems Foundations of Cyber-Physical Systems”, Springer, 2011.

4. Edward A.Lee and Sanjit A .Seshia: Introduction to Embedded Systems, A Cyber-Physical Systems Approach, Second Edition, MIT Press, ISBN978-0-262-53381-2,2017.

5. M.Wolf: Computers as Components–Principles of Embedded System Design. Morgan Kaufman Publishers , ISBN978-0-128-05387-4,2016.

6. Mazidi & Mazidi, “8051MicrocontrollerandEmbeddedSystems” Steve Furber,―ARM System-On-Chip Architecture, Second Edition, Pearson Publisher,2015.

7. Shibu K V, ―Introduction to Embedded Systems‖, Tata McGraw Hill Education Private Limited, 2009.

8. Steve Furber, ― ARM System-On-Chip Architecture‖, Second Edition, Pearson Publisher, 2015.

9. N. Sloss, D. Symes, and C. Wright, "ARM system developer's guide: Designing and optimizing and system software", Elsevier, 2008.

Course Number

EC5106

Course Credit

L-T-P-C: 3-0-2-4

Course Title

Semiconductor Device Modeling & Simulation

Learning Mode

Lectures and Labs

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Semiconductor Device Modeling & Simulation covers the principles and techniques for modeling the behavior of semiconductor devices. The course includes simulation methods for analyzing device performance and the impact of physical parameters on circuit functionality.

Course Outline

Two-terminal MOS device: threshold voltage modeling (ideal case as well as considering the effects of Φms and Dit.); C-V characteristics (ideal case as well as considering the effects of Qf, Qm and Dit); MOS capacitor as a diagnostic tool (measurement of non-uniform doping profile, estimation of Qm and Dit)

4-terminal MOSFET: threshold voltage (considering the substrate bias); above threshold I-V modeling (SPICE level 1,2,3 and 4); subthreshold current model; scaling; effect of threshold tailoring implant (analytical modeling of threshold voltage using box approximation); buried channel MOSFET; short channel, DIBL and narrow width effects; small signal analysis of MOSFETs (Meyer’s model) SOI MOSFET: basic structure; threshold voltage modeling

Advanced topics: hot carriers in channel; EEPROMs; CCDs; high-K gate dielectrics

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. D. G.Ong, “Modern MOS Technology: Processes, Devices and Design”, McGraw Hill, 1984.

2. Y. Taur and T. H. Ning, “Fundamentals of modern VLSI Devices”, Cambridge Univ. Press,

1998.

3. S.M. Sze, “Physics of Semiconductor Devices”, 3rd Edition, Wiley-Interscience, 2006

Course Number

EC5203

Course Credit

L-T-P-C: 3-0-2-4

Course Title

Analog and Mixed Signal Integrated Circuits

Learning Mode

Lectures and Labs

Learning Objectives

Complies with Program Goals 1, 2, 3 and 4

Course Description

Analog and Mixed Signal Integrated Circuits explore the design and analysis of circuits that process both analog and digital signals. The course covers topics such as amplifiers, filters, data converters, and their applications in modern electronics.

Course Outline

CMOS Opamp: Basics of Differential amplifier with active load. Two CMOS Opamp Design, Frequency compensation of the CMOS Opamp. Three stage Opamp with output buffer.

Reference circuits: Supply-insensitive biasing, Self-biased VTH-reference circuit, PTAT current generation, Temperature-insensitive biasing.

Switched capacitor circuits: Switched capacitor amplifiers, integrators and filters.

Non-Linear Analog Circuits: Basic CMOS Comparator Design, Analog Multipliers, Multiplying Quad, Level Shifting (Excluding Input Level Shifting For Multiplier).

Data converter fundamentals: Analog versus Digital Discrete Time Signals, Converting Analog Signals to Data Signals, Sample and Hold Characteristics, DAC Specifications, ADC Specifications, Mixed-Signal Layout Issues.

Data Converters Architectures: DAC Architectures, Digital Input Code, Resistors String, R-2R Ladder Networks, Current Steering, Charge Scaling DACs, Cyclic DAC, Pipeline DAC, ADC Architectures, Flash, 2-Step Flash ADC, Pipeline ADC, Integrating ADC, Successive Approximation ADC. Oversampling Sigma-Delta modulator and converters.

Learning Outcomes

Complies with PLOs 1a, 1b, 2, 3a and 3b

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. B. Razavi, “Design of Analog CMOS Integrated Circuits” 1st Edition, McGraw Hill, 2000.

2. P. E. Allen and D. R. Holberg, “CMOS Analog Circuit Design” 2nd Edition, Oxford University Press, 2002.

3. Paul Gray, P J Hurst, S H Lewis and R G Meyer, “Analysis and design of Analog Integrated Circuits”, Wiley

4. Sergio Franco, “Analog Circuit Design Discrete and Integrated”, McGrawHill

5. Walt Kester, “The Data Conversion Handbook,” Elsevier

6. Franco Maloberti, “Data Converters”, Springer

7. Rudy van de Plassche, “CMOS Integrated A/D and D/A Converters,” Springer

8. Shanthi Pavan, Richard Schreier, “Understanding Delta-Sigma Data Converters” IEEE-Wiley

9. R. Jacaob Baker, “CMOS- Mixed Signal Circuit Design '' (Vol ll of CMOS: Circuit Design, Layout and Simulation), IEEE Press and Wiley Interscience, 2002.

Course Number

EC5204

Course Credit

L-T-P-C: 3-0-2-4

Course Title

High Performance Embedded Computing System

Learning Mode

Lectures and Labs

Learning Objectives

Complies with Program Goals 1, 2, 3 and 4

Course Description

This course focus on the architecture and design of embedded systems that require high computational power. The course covers parallel processing, optimization techniques, and applications in areas such as signal processing and real-time computing.

Course Outline

Introduction and evolution of high-performance embedded computing system.

Basics of Computer Design & Performance Evaluation: Defining Computer Architecture, Quantitative Principles of Computer Design, CPU Performance & its factors, SPEC Benchmarks.

Computational model: Basic computational models, Abstract level of processor, Open Source ISA, Micro-Architecture,

High performance computer arithmetic architectures,

Instruction level Parallelisms: ILP concepts, Dependencies between instructions, preserving sequential consistency.

Pipelining: Introduction to pipelining, Instruction pipeline design, Pipeline hazards, deep pipeline microarchitecture and micro-operation,

Superscalar Processors: Introduction, Parallel decoding, Superscalar instruction issue, Shelving, Register Renaming,

Memory System: Memory hierarchy, Memory system Performance, Cache Memory, Cache Coherence, Memory Consistency, Cache Performance Issues, Shared Memory Organization. High performance Bus Architecture, Parallel-Virtual-Machine Architecture and programming model. Multicore and multiprocessor architecture, VLIW processor architectures. Array and vector processors.

Introduction Embedded Co-Processor: GPU and ML Accelerator

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. John L. Hennessy and David A. Patterson, “Computer Architecture-A Quantitative

Approach”, 6th Edition, Elsevier, 2019.

2. John L. Hennessy and David A. Patterson, “Computer Organization and Design”,

Morgan Kaufmann Publisher, 2nd Edition, 2021.

3. S. R. Sarangi, “Advanced Computer Architecture”, 1st Edition, 2021.

4. Sima, Fauntain, Kscucle, “Advanced Computer Architecture a design space approach”,

Pearson, 7th Edition, 2009.

5. Kai Hwang, “Advanced Computer Architecture”, McGrawHill publication, 2003.

 Note: for text 2 to 3, remaining for references

Course Number

EC5114

Course Credit

3-0-0-3

Course Title

Opto-Electronics Materials and Devices

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Opto-Electronics Materials and Devices cover the study of materials and devices that interact with light for applications in communication, sensing, and display technologies. The course includes topics such as semiconductor optoelectronics (e.g., LEDs, lasers, photodetectors), optical materials (e.g., semiconductors, polymers), device physics, fabrication techniques, and applications in telecommunications, imaging, solar cells, and optical sensing.

Course Outline

UNIT I ELEMENTS OF LIGHT AND SOLID-STATE PHYSICS

Wave nature of light, Polarization, Interference, Diffraction, Light Source, review of Quantum Mechanical concept, Review of Solid-State Physics, Review of Semiconductor Physics and Semiconductor Junction Device.

UNIT II DISPLAY DEVICES AND LASERS

Introduction, Photo Luminescence, Cathode Luminescence, Electro Luminescence, Injection Luminescence, Injection Luminescence, LED, Plasma Display, Liquid Crystal Displays, Numeric Displays, Laser Emission, Absorption, Radiation, Population Inversion, Optical Feedback, Threshold condition, Laser Modes, Classes of Lasers, Mode Locking, laser applications.

UNIT III OPTICAL DETECTION DEVICES

Photo detector, Thermal detector, Photovoltaics, Photo Conductors, Sensors, Detector Performance.

UNIT IV OPTOELECTRONIC MODULATOR

Introduction, Analog and Digital Modulation, Electro-optic modulators, Magneto Optic Devices, Acoustoptic devices, Optical, Switching and Logic Devices.

UNIT V OPTOELECTRONIC INTEGRATED CIRCUITS

Introduction, hybrid and Monolithic Integration, Application of Opto Electronic Integrated Circuits, Integrated transmitters and Receivers, Guided wave devices.

Learning Outcome

Complies with PLO 1b, 2a and 4a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text Books

1. Pallab Bhattacharya “Semiconductor Opto Electronic Devices”, Prentice Hall of India

Pvt., Ltd., New Delhi, 2006.

2. Jasprit Singh, “Opto Electronics – As Introduction to materials and devices”,

McGraw-Hill International Edition, 1998

 Reference Books

1. S C Gupta, Opto Electronic Devices and Systems, Prentice Hal of India,2005.

2. J. Wilson and J.Haukes, “Opto Electronics – An Introduction”, Prentice Hall, 1995.

Course Number

EC5115

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Radio Frequency Integrated Circuits

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Radio Frequency Integrated Circuits (RFIC) focus on the design and implementation of circuits operating at radio frequencies. The course covers topics such as RF amplifiers, mixers, oscillators, and their applications in wireless communication systems.

Course Outline

Introduction to RF and Wireless technology; Basic concepts in RF & Wireless Integrated Circuits Design; Receiver and Transmitter Architectures.

Low Noise RF Amplifiers – Electrical Noises, Two port Noise theory, LNA characteristic parameters and basic topologies, Input impedance and Noise Figure of amplifiers e.g Inductively degenerated, Differential LNA; Broadband Amplifier and amplifier Stability;

Mixers – Mixer Operation and linearity, Passive and Active Mixers, Single & Double-Balanced Mixers, Conversion Gain and Port-to-Port Feedthrough (or leakage), Image Reject and Single Sideband Mixers, Noise in Mixers;

Oscillators – Oscillator as a Feedback System, Negative Resistance Oscillator Model; LC Oscillators - Colpitts, Hartley, Clapp, Pierce crystal Oscillators, Quadrature Oscillators; Ring oscillators, Voltage Controlled-Oscillator, Phase Noise and Jitter in Oscillators;

Frequency Synthesizers – Phase Locked Loop (PLL), Analysis of PLL Synthesizers, Phase Noise in PLL Synthesis, PLL Frequency Synthesizers, Integer-N and Fractional-N PLL Synthesizers, PLL System Frequency Response and Bandwidth;

RF Power Amplifiers – Efficiency, Analysis of Basic Classes – A, AB, B, C, Class B Push-Pull Arrangements, Switch mode Classes – D, E, F Amplifiers, Doherty Power Amplifier, Linearization Techniques.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text

1. Thomas H Lee, The Design of CMOS Radio Frequency Integrated Circuits, Cambridge     University Press

2. Behzad Razavi, RF Microelectronics, 2/e, Pearson India.

3. David M Pozar, Microwave and RF Design of Wireless Systems, John Wiley and Sons

4. Steven Cripps, RF Power amplifier for wireless communications, Artech House

5. Herbert Krauss, Charles Bostian, and Frederick Raab, Solid state radio engineering, John Wiley and Sons

6.  Andrei Grebennikov, Marc J. Franco Switchmode RF and Microwave Power Amplifiers, Academic Press Inc

References

1. John W M Rogers and Calvin Plett, Radio Frequency Integrated Circuit Design, Artech House, Boston.

2. Frank Ellinger, Radio Frequency Integrated Circuits and Technologies, Springer

3. Richard C-H Li, RF Circuits Design, John Wiley 

4. Les Besser and Rowan Gilmore, Practical RF Circuit Design for Modern Wireless Systems, vol. 2, Artech House, Boston

Course Number

EC5116

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Advanced Digital Image Processing

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Advanced Digital Image Processing involves the manipulation and analysis of digital images using computational algorithms. The course covers topics such as image enhancement, restoration, segmentation, feature extraction, and compression. It also includes applications in fields such as medical imaging, remote sensing, robotics, and multimedia systems.

Course Outline

DIGITAL IMAGE FUNDAMENTALS:   Elements of Visual Perception; Image Sensing and Acquisition; Image Sampling and Quantization; Basic Relationships between Pixels; Monochromatic Vision Models; Colour Vision Models; Colour Fundamentals; Colour Models; Conversion of Colour Models; Colour Transformations.

ENHANCEMENT & RESTORATION : Homomorphic filtering, inverse and minimum error filtering,  Noise types and related filtering.

IMAGE ANALYSIS AND REPRESENATION: Introduction; Image Segmentation - Point, Line, Edge, Boundary Detection; Colour Image Segmentation;  Thresholding- Basic Global Thresholding, Multiple Thresholding, Variable Thresholding; Region Based Segmentation;  Representation: Chain codes, Signatures, Boundary segments, Skeletons, Description: Boundary Descriptors, Regional Descriptors.

MORPHOLOGICAL PROCESSING & COMPRESSION:  Morphological Image Processing – Logic Operations involving Binary Images; Dilation and Erosion; Basic Morphological Algorithms – Boundary Extraction, Region Filling, Thickening                    

Image Compression – Compression Model, Different Coding schemes like Arithmetic Coding, LZW coding etc. Baseline jpeg, jpeg 2000, Mpeg etc.

CLASSIFICATION AND APPLICATIONS of Object Recognition and Classification, Statistical classification, Structural /Syntactic Classification,  3D Image Processing, 3D Visualization: Surface rendering, Volume rendering;          

Applications: Motion Analysis, Image Fusion, Image super resolution

 Learnng Outcome

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1.      1. Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Pearson

2.      2. Milan Sonka, Vaclav Hlavac and Roger Boyle, Image Processing, Analysis and Machine Vision, Springer

3.      3. Anil K. Jain, Fundamentals of Digital Image Processing, Prentice Hall

Course Number

EC5117

Course Credit

L-T-P-C: 3-0-0-3

Course Title

VLSI Testing and Verification

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

VLSI Testing and Verification covers methodologies and techniques for ensuring the correctness and reliability of Very-Large-Scale Integration (VLSI) circuits. The course includes topics such as test pattern generation, fault simulation, design for testability (DFT), and verification methodologies using simulation and formal methods.

Course Outline

Testing Philosophy, Role of Testing, Digital and Analog VLSI Testing, Test Economics, Defects, Errors, and Faults Levels of Fault Models, Controllability and Observability. Algorithms and Representations: Structural vs. Functional Test, Search Space Abstractions ATPG Algebras, Redundancy Identification, Combinational ATPG Algorithms, Test Generation Systems, Simulation-Based Sequential Circuit ATPG, Complexity of Sequential ATPG. Memory Test: Memory Density and Defect Trend, Memory Test Levels, Fault Modeling, Memory Testing Delay Test, IDDQ test, Design for Testability. Built in Self-test.

Design Verification: The importance of verification, Reconvergence model, Formal verification, Equivalence checking, Model checking, Functional verification. Verification Tools. Simulators: Stimulus and response, Event based simulation, cycle-based simulation, Co-simulators, verification intellectual property: hardware modelers, The verification plan: The role of verification plan: specifying the verification plan, defining the first success. Levels of verification: unit level verification, reusable components verification, ASIC and FPGA verification, system level verification, board level verification, verifying strategies, verifying responses.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. P. K. Lala, “Digital Circuit Testing and Testability”, Academic Press, 1997.

2. M. L. Bushnell and V.D. Agrawal, “Essentials of Electronic Testing for Digital, Memory and Mixed-Signal VLSI Circuits”, Kluwar Academic Publishers 2002.

3. M. Abramovici, M.A. Breuer and A.D. Friedman, "Digital Systems and Testable Design", Jaico Publishing House, 2002.

4. Janick Bergeron, “Writing Test benches: functional verification of HDL models”, 2nd Edition, Kluwer Academic Publishers, 2003

5. Jayaram Bhasker and Rakesh Chadha, “Static Timing Analysis for Nanometer Designs” A practical approach, 1st Edition, Springer publications, 2009.

6. Prakash Rashinkar, Peter Paterson, Leena Singh “System on a Chip Verification”, Kulwer Publications, 2002.

Course Number

EC5118

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Bio Sensors and Circuits

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Bio Sensors and Circuits focus on the design and implementation of circuits and systems for biological sensing applications. The course covers topics such as sensor technologies (e.g., optical, electrochemical), signal conditioning, data acquisition, and integration with biological systems for healthcare monitoring, environmental sensing, and biomedical research.

Course Outline

Transducers Principles, Biochemical Transducers: Electrode theory, electrode impedance, metal-electrolyte interface and electrode-tissue interface, Bio-potential electrodes: microelectrodes, body surface electrodes, needle electrodes, electrodes for ECG, EEG, and EMG. Electrodes: hydrogen electrodes, Ag/AgCl electrodes, Calomel electrodes, specific ion electrodes, pH electrode, O2 and CO2 electrode, Optical Sensor and Radiation Detectors: Principles of optical sensors and types of optical sensors, Optical fibers, LASERs, Radiation detectors: Proportional counter, Gas-ionization chamber, Geiger counters, Scintillation detectors., Biological Sensors: Receptors in the human body, Ion exchange membrane electrodes, enzymatic biosensors, Basic principles of MOSFET biosensors & BIOMEMS, basic idea about Smart sensors, Biomedical Measurement

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. Josheph J. Carr and John M. Brown, “Introduction to Biomedical Equipment Technology”, 4th Edition, Pearson Education, 2001.

2. John. G. Webster, “Medical Instrumentation- Application and Design”, 4th Edition, John Wiley & Sons, 2010.

3. Willis J. Tompkins, “Biomedical Digital Signal Processing” Prentice-Hall of India, 1993.

4. Rangraj M. Rangayyan, “Biomedical Signal analysis- A Case Study Approach”, Wiley India Pvt. Ltd., 2009.

5. Suresh R. Devashahayan, “Signals and Systems in Biomedical Engineering”, Revised 2nd Edition, Kluwer academics/ Plenum publication, 2013.

6. Josheph J. Carr and John M. Brown, “Introduction to Biomedical Equipment Technology”,4th Edition, Prentice Hall, 2000.

7. Leslie Cromwell, Fred J. Weibell, and Erich A. Pfeiffer “Biomedical Instrumentation and Measurements”, 2nd Edition, Prentice-Hall of India, 2000.

Course Number

EC6105

Course Credit

L-T-P-C: 3-0-0-3

Course Title

CMOS Phase-Locked Loops

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

CMOS Phase-Locked Loops (PLLs) involve the design and implementation of frequency synthesis circuits using Complementary Metal-Oxide-Semiconductor (CMOS) technology. The course covers topics such as PLL architecture, phase detection and comparison, loop filter design, voltage-controlled oscillator (VCO) characteristics, and applications in clock generation, frequency synthesis, and communication systems.

Course Outline

Introduction to PLL, Various types of PLL

PLL building blocks: Phase detectors, Phase/Frequency detectors, Ring and LC Voltage-controlled Oscillators (VCO), Frequency Dividers

Analysis of PLL: Type-I and Type-II 2nd order PLL; Higher-order loop filters and PLL; PLL Stability

Designing PLL: a 2nd order PLL

Jitter and Phase noise in Oscillators and PLLs,

PLL-based frequency synthesizer: Integer-N and Fractional-N synthesizers, Δ∑ Fractional-N synthesizers

All-Digital PLL: Time-to-Digital Conversion, Digital Filters, Digitally Controlled Oscillators,

Delay-locked Loops

Low jitter frequency synthesizer: Subsampling PLL Architecture and it components

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. B. Razavi, “Design of CMOS Phase-Locked Loops” Cambridge Univ Press, 2020.

2. William F Egan, “Phase-lock Basics,” IEEE-Wiley

3. Floyd M. Gardner, “Phase Lock Techniques” 3rd Edition, Wiley-inter-science

4. Ronald E Best, “Phase-locked Loop, Design, Simulation and Applications”, 6th edition, McGrawHill

5. Venceslav F Kroupa, “Phase Lock Loops and Frequency Synthesis,” Wiley

6. Shanthi Pavan, Richard Schreier, “Understanding Delta-Sigma Data Converters” IEEE-Wiley

Course Number

EC5111

Course Credit

L-T-P-C: 3-0-0-3

Course Title

VLSI Architectural Design and Implementation

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

VLSI Architectural Design and Implementation covers the principles of designing and implementing efficient VLSI architectures. The course includes topics such as pipeline design, data path optimization, and hardware description languages.

Course Outline

Introduction to VLSI System Design and Implementation; Architectural mapping with case studies: Data path, Control path Synthesis; Control Strategies: Hardware implementation of various control structures; Micro-program control techniques; Design issues: Timing, Area, power analysis; FSM Architecture and Synthesis, HDL design and implementation of VLSI architecture;

Semiconductor Memory and Peripheral Architectures; Computer arithmetic architecture design and analysis: Introduction to integer and floating-point arithmetic, Adders, Subtractors, Sequential and Array multipliers & dividers, square root, Absolute Difference Value, CORDIC.

Hardware architecture design and performance analysis: Sequential/Folding architectures; bit and word serial architecture; High performance architectures: pipelined, parallel and Systolic Array with examples; Architectural performance Analysis: Throughput and Latency; Low Power VLSI Architectures; Basic Hardware Architectures for Digital Signal processing and machine learning algorithms.

Introduction to VLSI Chip testing methods and Architectures: Introduction to Chip Fault Model, DFT Architecture, BIST Architecture.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. Peter Pirsch, "Architectures for Digital Signal Processing", John Willy & sons,2nd Edition,2014.

2. K. K. Parhi, " VLSI Digital Signal Processing Systems: Design and Implementation", A Wiley-Interscience publications,2011.

3. Behrooz Parhami, " Computer Arithmetic: Algorithm and Hardware Design", Behrooz Parhami, Oxford University Press, 2nd Edition,2009.

4. A. Bellaouar, M. I. Elmarsny, "Low Power Digital VLSI Design", A. Bellaouar, M. I. Elmarsny, Kluwe academic Publication,1995.

5. DSP Integrated Circuit, L. Wamhammer, Academic Press,1999.

Course Number

EC5119

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Quantum Computing

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Quantum Computing explores the theory and practical applications of quantum mechanics in computing. The course covers quantum algorithms, quantum gates, qubits, and their potential impact on cryptography, optimization, and simulation problems.

Course Outline

Introduction: History, Motivation, Need of quantum bits, quantum states, quantum computations, quantum information, and quantum algorithms. Overview of complex numbers and Linear Algebra, Introduction to quantum mechanics and its postulates, Bloch sphere

Quantum Circuits: Single qubits and multiple quibits operations, architecture, quantum gates; quantum teleportation, quantum Fourier Transform: phase estimation

Quantum Algorithms: Deutsch’s algorithm, Deutsch-Jozsa algorithm, Simon’s algorithm, Grover algorithm and Shor’s factoring algorithm. Quantum Information and Error Corrections: Classical vs quantum noise, quantum operations, quantum error correction, entropy and information

Quantum Tools and Applications: Goal Challenges, Lights and Photon, Decoherence, Ion Trap, Linear Optics, NMR, Quantum Simulation

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. Nielsen, Michael A., and Isaac L. Chuang. Quantum computation and quantum information. Cambridge university press, 2010.

2. Yanofsky, Noson S., and Mirco A. Mannucci. Quantum computing for computer scientists. Cambridge University Press, 2008.\

3.  Johnston, Eric R., Nic Harrigan, and Mercedes Gimeno-Segovia. Programming quantum computers: essential algorithms and code samples. O'Reilly Media, 2019.

Course Number

EC5120

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Semiconductor Packaging Technology

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Semiconductor Packaging Technology focuses on the methods and materials used to protect, connect, and enhance the reliability of semiconductor devices. The course covers topics such as packaging types (e.g., flip-chip, wire-bonding), thermal management, and reliability testing for various electronic applications.

Course Outline

Introduction to IC Packaging • Definition of packaging and its significance in various industries.   • Introduction to packaging and its importance in Modern Electronics.  

Traditional Packaging Technologies • Exploring different packaging technologies, such as leaded and leadless packages, surface mount technology (SMT), and ball grid array (BGA).  Discussion on the purpose and characteristics of each technology.   • Explanation of the factors influencing technology selection. Introduction to Advanced Packaging • Definition of advanced packaging and its importance in meeting evolving technology requirements.  Explaining the benefits and challenges associated with advanced packaging.    • Exploring different integrated technology of advanced packaging technologies, such as 2.5D, 3D packaging, 

Advanced Packaging Interconnects: Discussion on interconnect technologies used in advanced packaging, such as flip chip bumping, solder balls, and through-silicon vias (TSVs), photonic integration.

 Testing and Reliability in Advanced Packaging: The testing methodologies and reliability considerations specific to advanced packaging.   • Discussion on package-level testing, interconnect testing, and reliability testing. Explanation of various failure analysis techniques and strategies for ensuring package reliability.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Textbooks

1.      Yoshio Nishi and Robert Doering, "Handbook of Semiconductor Manufacturing Technology" 2^nd Edition, CRC Press, 2017.

2.      Simon M. Sze, Ming-Kwei Lee , "Semiconductor Devices: Physics and Technology"  Wiley, 2012.

3.      John H. Lau  " Semiconductor Advanced Packaging", Springer, 2021.

References

1.      Christopher Bower, Peter Ramm, Philip Garrou , "Handbook of 3D Integration: Technology and Applications of 3D Integrated Circuits", Wiley, 2011.

2.      Behzad Razavi, "Fundamentals of Microelectronics", Wiley, 2014.

Course Number

EC6104

Course Credit

L-T-P-C: 3-0-0-3

Course Title

VLSI Signal Processing

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

VLSI Signal Processing involves the design and implementation of signal processing algorithms and systems using Very-Large-Scale Integration (VLSI) technology. The course covers topics such as digital signal processing (DSP) algorithms, efficient hardware implementations, optimization techniques, and applications in areas such as telecommunications, audio processing, image processing, and biomedical signal processing.

Course Outline

Introduction to DSP systems: Representation of DSP algorithms; Iteration Bound: Definition, Examples, Algorithms for computing Iteration bound; Pipelining and Parallel Processing: Definitions, Pipelining and parallel processing of FIR filters, Pipelining and parallel processing for low power; Retiming: Definitions and Properties, Solving system of Inequalities, Retiming techniques; Unfolding: Definition, An algorithm for unfolding, Applications of unfolding; Folding: Definition, Folding transformations, Register minimization techniques, Register minimization in folded architectures; Systolic Architecture Design: Introduction, Systolic array design methodology, FIR systolic arrays, Selection of scheduling vector, Matrix-Matrix multiplication and 2D systolic array design; CORDIC based Implementations: Architecture, Implementation of FIR filter and FFT algorithm; Bit-Level arithmetic architectures: Parallel multipliers, Bit-serial multipliers, Bit-Serial FIR filter design and Implementation; Redundant arithmetic: Redundant number representation, Carry-free radix-2 addition and subtraction, radix-2 hybrid redundant multiplication architectures; Low-power design: Theoretical background, Scaling versus power consumption, Power analysis, Power reduction techniques, Power estimation approaches.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. U. Meyer-Baese, “DSP with FPGA”, Springer,4th Edition, 2014.

2. K. K. Parhi, “VLSI DSP Systems”, Wiley, 2003.

3. R.G. Lyons, “Understanding Digital Signal Processing”, Pearson Education,3rd Edition, 2011.

Course Number

EC6102

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Computer Vision

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Computer Vision involves the development of algorithms and systems that enable computers to interpret visual information from the real world. The course covers topics such as image processing, object detection and recognition, image segmentation, feature extraction, 3D reconstruction, and deep learning techniques applied to visual data. Applications include autonomous vehicles, medical imaging, surveillance, augmented reality, and robotics.

Course Outline

Computer vision introduction, image formation, perspective projection, camera response & HDR imaging, nature of image sensors, image filtering, template matching, Fourier transform, convolution and deconvolution,  edge and corner detection, canny edge detection,  Active contours, Hough transform, SIFT detector and descriptor, Image homography, Image warping and image blending, Face detection, nearest neighbor classifier, support vector machine, Radiometry and reflectance property, Photometric stereo, reflectance map, shape from normal, shape from shading, stereographic projection, shading illusion, dept from focus and depth from defocus, photometric stereo systems, camera calibration, simple stereo, uncalibrated stereo, epipolar geometry, stereo vision in nature, optical flow, Lucas Kanade method, structure from motion, object tracking, gaussian mixture model, feature detection for tracking, image segmentation by k-means, mean-shift and graph cut based methods. PCA and SVD and shape verses appearance. Neural network, Gradient descent, back propagation algorithm.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text

1.      Computer Vision - A modern approach, by D. Forsyth and J. Ponce, Prentice Hall Robot Vision, by B. K. P. Horn, McGraw-Hill.

References

       1. Computer Vision: Algorithms and Applications:  Richard Szeliski

2.  Foundations of Computer Vision Antonio Torralba (Author), Phillip Isola (Author), William T. Freeman (Author)

Course Number

EC5205

Course Credit

3-0-0-3

Course Title

Pattern Recognition and Machine Learning 

Learning Mode

Lectures

Learning Objectives

Course Learning Outcome (CLO): After learning this course, the students will be able 

1. to know various tools and techniques of pattern recognition. 

2. to develop skills to characterize and implement big data analytics. 

3. to understand the application of pattern recognition in different real-life problems.

Course Description

This course deals with the Pattern recognition and ML.

Course Outline

Introduction: Feature extraction and Pattern Representation, Concept of Supervised and Unsupervised Classification, Introduction to Application Areas. Statistical Pattern Recognition: Bayes Decision Theory, Minimum Error and Minimum Risk Classifiers, Discriminant Function and Decision Boundary, Normal Density, Discriminant Function for Discrete Features, Parameter Estimation. Dimensionality Problem: Dimensionality Reduction, Fisher Linear Discriminant and Multiple Discriminant Analysis. Nonparametric Pattern Classification: Density Estimation, Nearest Neighbour Rule, Fuzzy Classification. Linear Discriminant Functions: Separability, Two Category and Multi Category Classification, Linear Discriminators, Perceptron Criterion, Relaxation Procedure, Minimum Square Error Criterion, Widrow-Hoff Procedure, HoKashyap Procedure, Kesler’s Construction. Neural Network Classifier: Single and Multilayer Perceptron, Back Propagation, Learning Hopfield, Network Fuzzy and Neural Network. Time Varying Pattern Recognition: First Order Hidden Markov, Model Evaluation, Decoding Learning. Unsupervised Classification: Clustering, Hierarchical Clustering, Graph Based Method, Sum of Squared Error Technique, Iterative Optimization. 

Learning Outcome

Complies with PLO 1b, 2a and 4a

Assessment Method

Quiz, Assignments, and Exams

Suggested Readings

Texts/References: 

1. Richard O. Duda, Peter E. Hart and David G. Stork, Pattern Classification, John Wiley & Sons, 2001. 

2. Earl Gose, Richard Johsonbaugh and Steve Jost, Pattern Recognition and Image Analysis, Prentice Hall, 1999. 

Course Number

EC5206

Course Credit

3-0-0-3

Course Title

Multimedia Communication

Learning Mode

Lectures

Learning Objectives

After learning this course, the students will be able 

1. to understand the fundamental knowledge on multimedia system and Multimedia Communication. 

2. to understand the knowledge on Multimedia Information Systems. 

3. to understand the real-time constraints in Multimedia Communication. 

4. to develop problem statement on Multimedia Communication for research direction

Course Description

This course deals with the Multimedia Communication.

Course Outline

 Introduction to Multimedia System: Architecture and components, Multimedia distributed processing model, Synchronization, Orchestration and Quality of Service (QOS) architecture. Audio and Speech: Data acquisition, Sampling and Quantization, Human Speech production mechanism, Digital model of speech production, Analysis and synthesis, Psycho-acoustics, low bit rate speech compression, MPEG audio compression. Images and Video: Image acquisition and representation, Composite video signal NTSC, PAL and SECAM video standards, Bilevel image compression standards: ITU (formerly CCITT) Group III and IV standards, JPEG image compression standards, MPEG video compression standards. Multimedia Communication: Fundamentals of data communication and networking, Bandwidth requirements of different media, Real time constraints: Audio latency, Video data rate, multimedia over LAN and WAN, Multimedia conferencing. Hypermedia presentation: Authoring and Publishing, Linear and non-linear presentation, Structuring Information, Different approaches of authoring hypermedia documents, Hyper-media data models and standards. Multimedia Information Systems: Operating system support for continuous media applications: limitations is usual OS, New OS support, Media stream protocol, file system support for continuous media, data models for multimedia and hypermedia information, content based retrieval of unstructured data. 

Learning Outcome

Complies with PLO 1b, 2a and 4a

Assessment Method

Quiz, Assignments, and Exams

Suggested Readings

Text Books: 

1. J. D. Gibson, Multimedia Communications: Directions and Innovations, 2000, Elsevier. 

2. A. Puri and T. Chen, Multimedia Systems, Standards, and Networks, 1st Edition, 2000, CRC Press. 

5. Iain E.G. Richardson, H.264 and MPEG-4 Video Compression, 2004, John Wiley & Sons. 

Reference Books:

1. Ralf Steinmetz and Klara Nahrstedt, Multimedia Systems, 2004, Springer. 

2. K. Sayood, Introduction to Data Compression, 2017, Morgan-Kaufmann. 

3. Borivoje Furht, Handbook of Multimedia Computing, 1998, CRC Press

Course Number

EC5214

Course Credit

L-T-P-C: 3-0-0-3

Course Title

VLSI Technology

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

VLSI Technology focuses on the processes and methodologies used in the fabrication of Very-Large-Scale Integration circuits. The course covers semiconductor materials, photolithography, etching, doping, and the integration of components into complex systems.

Course Outline

General Overview of current status of VLSI Technology- Interaction between Technology and Design, - Interaction between Physics and Technology, - Limits of Technology, Environment for Integrated Circuits Manufacture, - Clean Rooms and Wafer cleaning procedures., - Technology

Processes in Fabrication, - Oxidation, Diffusion, Ion Implantation, Etching and Deposition,

techniques., - Characterization of Processes.

Lithography and Mask generation techniques - Advanced Unit-Processors for ULSI Circuit

Technologies., - Use of RTP, - Plasma processes in the fabrication in the fabrication of circuits., Basic

Bipolar process Technologies., NMOS Technology, Mask sequence based fabrication process for NMOS transistors, - Silicon Gate and Metal Gate

Technologies. Limitations of NMOS Technology.

CMOS Technology - Process Sequence for CMOS Technology, Advanced CMOS Processes,

“Design – Rules” for NMOS and CMOS Technologies as “Constraints” for Layouts.

Process Simulation - Use of SUPREM-IV ans STEP Simulators for process Design, - Some

Examples of actual technologies.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. S.K. Gandhi, “VLSI Fabrication principles”, John Wiley Inc., New York, 1983

2. S.M. Sze “VLSI Technology”, 2nd Edition, McGraw Hill Co. Inc., New York, 1988

3. C. Y. Chang and S. M. Sze, “VLSI Technology”, McGraw Hill Co. Inc., New York, 1996

Course Number

EC5215

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Sensors and Actuators

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Sensors and Actuators involve the study and application of devices that sense physical quantities (sensors) and act upon them (actuators). The course covers principles of transduction, sensor types (e.g., optical, pressure, temperature), actuator mechanisms (e.g., motors, valves), interfacing with electronics, and applications in various fields such as automotive, healthcare, and industrial automation.

Course Outline

Brief overview of measurement systems, classification, characteristics and calibration of different sensors. Measurement of displacement, position, motion, force, torque, strain gauge, pressure flow, temperature sensor sensors, smart sensor. Optical encoder, tactile and proximity, ultrasonic transducers, opto-electrical sensor, gyroscope. Principles and structures of modern micro sensors, micro-fabrication technologies: bulk micromachining, surface micromachining, LIGA, assembly and packaging. Pneumatic and hydraulic systems: actuators, definition, example, types, selection. Pneumatic actuator. Electro-pneumatic actuator. Hydraulic actuator, control valves, valve sizing valve selection. Electrical actuating systems: solid-state switches, solenoids, voice coil; electric motors; DC motors, AC motors, single phase motor; 3-phase motor; induction motor; synchronous motor; stepper motors. Piezoelectric actuator: characterization, operation, and fabrication; shape memory alloys.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. John G. Webster, Editor-in-chief, “Measurement, Instrumentation, and Sensors Handbook”, CRC Press (2014).

2. Jacob Fraden, “Handbook of modern Sensors”, AIP Press, Woodbury (2016).

3. Nadim Maluf, “An Introduction to Microelectromechanical Systems Engineering”, Artech House Publishers, Boston (2004).

4. Marc Madou, “Fundamentals of Microfabrication”, CRC Press, Boca Raton (2002).

5. Gregory Kovacs, “Micromachined Transducers Sourcebook”, McGraw-Hill, New York (1998).

6. E. O. Deobelin and D. Manik, “Measurement Systems – Application and Design”, Tata McGraw-Hill (2004).

7. D. Patranabis, “Principles of Industrial Instrumentation”, Tata McGraw-Hill, eleventh reprint (2004).

8. B. G. Liptak, “Instrument Engineers’ Handbook: Process Measurement and Analysis”, CRC (2003).

Course Number

EC6209

Course Credit

L-T-P-C: 3-0-0-3

Course Title

MEMS and NEMS

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

MEMS (Microelectromechanical Systems) involve the integration of mechanical elements, sensors, actuators, and electronics on a single semiconductor substrate at a microscale level. The course covers fabrication techniques, design principles, and applications in fields such as automotive, biomedical devices, and consumer electronics.

Course Outline

MEMS and Microsystems, Miniaturization, Typical products, Micro sensors, Micro actuation, MEMS with micro actuators, Micro-accelerometer’s and Micro fluidics, MEMS materials, Micro fabrication , Elasticity, Stress, strain and material properties, Bending of thin plates, Spring configurations, torsional deflection, Mechanical vibration, Resonance, Thermo mechanics – actuators, force and response time, Fracture and thin film mechanics. Electrostatics: basic theory, electro static instability. Surface tension, gap and finger pull up, Electro static actuators, Comb generators, gap closers, rotary motors, inch worms, Electromagnetic actuators. bistable actuators. Electronic Interfaces, Feedback systems, Noise , Circuit and system issues, Case studies – Capacitive accelerometer, Peizo electric pressure sensor, Modelling of MEMS systems, CAD for MEMS. Optical MEMS, - System design basics – Gaussian optics, matrix operations, resolution. Case studies, MEMS scanners and retinal scanning display, Digital Micro mirror devices. RF Memes – design basics, case study – Capacitive RF MEMS switch, performance issues   

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text

1. Stephen Santuria, “Microsystems Design”, Kluwer publishers, 2000.

References

References

1. Nadim Maluf, “An introduction to Micro electro mechanical system design”, Artech House, 2000

2. Mohamed Gad-el-Hak, editor,” The MEMS Handbook”, CRC press Baco Raton, 2000.

3. Tai Ran Hsu, “MEMS & Micro systems Design and Manufacture”, Tata McGraw Hill, New Delhi, 2002.

Course Number

EC6210

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Advance FPGA Platform and System

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Advance FPGA platform and system focuses on the methods of design, development and  implementation of complex digital systems using advanced Field-Programmable Gate Arrays (FPGAs) fabrics platform. The course covers topics such as advance FPGA architecture, design methodologies, IP core integration, and implementation of Digital signal processing, control  and communication Systems. It also highlights the methods and tools for implementation of Machine learning algorithms.

Course Outline

Introduction to reconfigurable and FPGA based system Design; Basic and Advanced FPGA Fabrics; Combinational and Sequential logic realization on FPGA;   Issues on FPGA based system Design: Area, Timing and Power; Design; Behavioral /high level Design and implementation methodologies: HDL,  IP Core, System Generator;  Processor and memory cores; Timing analysis; Clock distribution and management systems; Large scale System Design: Platform FPGA,  Multi-FPGA System; Busses and I/O communication system;  DSP system Design and Implementation using FPGA;  FPGA based Embedded system platform: Design and implementation methods. Introduction to Implementation methods and tools for machine learning algorithms. Advance FPGA for real time application: A Case Studies on signal processing, Communication and control systems.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1.      Steve Kilts, “Advanced FPGA design – Architecture, Implementation and Optimization”,  Wiley publications,2007.7. Samir Palnitkar, “Verilog HDL: A Guide to Digital Design and Synthesis”, Second Edition, Prentice Hall PTR, 2003.

2.    Wayne Wolf, “FPGA-Based System Design”, Prentice Hall Modern Semiconductor Design Series, 

       2004.

3.   Ron Sass and Andrew G. Schmidt, Morgan Kaufmann (MK), “Embedded System design with 

      Platform FPGAs”, Elsevier,2010.

Course Number

EC5216

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Low power VLSI

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Low Power VLSI focuses on techniques and strategies for reducing power consumption in Very-Large-Scale Integration (VLSI) circuits. The course covers power-aware design, optimization methods, and applications in portable and energy-efficient devices.

Course Outline

Need for Low Power Circuits, Low Power Techniques at different Hierarchical levels; CMOS basics: MOS Transistors, Short Channel Effects, Spice models for MOS transistors, MOS Invertors characteristics, Delay Estimation, BICMOS logic circuits; MOS Logic Styles: Static CMOS, Dynamic CMOS and Pass transistor circuits; Sources of Power dissipation: Diode Leakage Power, Short Circuit Leakage Power, Switching Power and Switching Activity of Static and Dynamic Circuits, Parameters involved in power dissipation; Low-power Design Methodologies: Supply voltage scaling approaches at different levels of hierarchy, Multi-threshold CMOS circuit design, Dynamic Voltage Scaling, Minimizing Switched Capacitance at different levels; Adiabatic switching concepts; Low Power CMOS RAM Circuits.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. Ajit Pal, “Low-Power VLSI Circuits and Systems”, Springer, 2015

2. J. B. Kuo and J-H. Lou, “Low-Voltage CMOS VLSI Circuits”, Wiley, 1999.

3. K. Roy and S. C. Prasad, “Low-Power CMOS VLSI Circuit Design”, Wiley, 2000.

Course Number

EC5217

Course Credit

L-T-P-C: 3-0-0-3

Course Title

CAD VLSI

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

CAD VLSI (Computer-Aided Design for Very-Large-Scale Integration) involves the use of software tools and methodologies to design, simulate, and verify integrated circuits. The course covers topics such as layout design, logic synthesis, timing analysis, and physical design automation (PDA) for efficient and reliable VLSI circuit design.

Course Outline

Introduction: VLSI design flow, challenges. Verilog/VHDL: introduction and use in synthesis, modeling combinational and sequential logic, writing test benches. Logic synthesis: two-level and multilevel gate-level optimization tools, state assignment of finite state machines. Basic concepts of high-level synthesis: partitioning, scheduling, allocation and binding. Technology  mapping. Testability issues: fault modeling and simulation, test generation, design for testability, built-in self-test. Testing SoC s. Basic concepts of verification. Physical design automation. Review of MOS/CMOS fabrication technology. VLSI design styles: full-custom, standard-cell, gate-array and FPGA. Physical design automation algorithms: floor-planning, placement, routing, compaction, design rule check, power and delay estimation, clock and power routing, etc. Special considerations for analog and mixed-signal designs.

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. Naveed Shervani, “Algorithms for VLSI physical design Automation”, 2nd Edition, Kluwer Academic Publisher, 1999. Christophan Meinel and Thorsten Theobold, “Algorithm and Data Structures for VLSI Design”,  KAP, 2002.

2. Rolf Drechsheler, “Evolutionary Algorithm for VLSI”, 2nd  Edition

3. Trim burger, “Introduction to CAD for VLSI”, Kluwer Academic publisher, 2002.

4. Randal L and Schwartz Tom Phoenix, “Learning PERL”, Oreilly Publications, 3rd Edition, 2000.

5. Samir Palnitkar, “Verilog HDL: A Guide to Digital Design and Synthesis”, Second Edition, Prentice Hall PTR, 2003.

Course Number

EC6211

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Hardware Security System

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

A Hardware Security System focuses on protecting electronic hardware from various threats, including unauthorized access, tampering, and exploitation. The course typically covers topics such as secure hardware design principles, cryptographic algorithms, side-channel attacks, physical unclonable functions (PUFs), and hardware/software co-design for secure systems in applications ranging from IoT devices to critical infrastructure.

Course Outline

Review of modular arithmetic, Groups, rights and Fields, Polynomial fields, Galois Field arithmetic. Mapping between Binary and Composite Fields.   Overview of Modern Cryptography: Stream ciphers, Block Ciphers, DES, AES, Rijndael in Composite Field, Elliptic Curves, Montgomery’s Algorithm for Scalar Multiplication.  Modern Hardware Design:  FPGA architecture, Mapping an Algorithm to Hardware, Hardware Design of Cryptographic Algorithms.  Overview of Different Issues of Hardware Security, Useful hardware Security Primitives, Side-channel Attacks on Cryptographic Hardware, Testability and Verification of Cryptographic Hardware, Modern IC Design and Manufacturing Practices and Their Implications, Hardware Trojans. Differential Fault Analysis of Ciphers

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1.     Christof Paar, Jan Pelzl, "Introduction to Cryptography" Springer 2010, ISBN: 978-3-642-44649-8 (Print) 978-3-642-04101-3 (Online)

2.     Ingrid Verbauwhede (Eds), "Secure Integrated Circuits and Systems" Springer 2010, ISBN: 978-0-387-71827-9 (Print) 978-0-387-71829-3 (Online) Stefan Mangard, Elisabeth Oswald, Thomas Popp, "Power Analysis Attacks," Springer 2007, ISBN: 978-0-387-30857-9 (Print) 978-0-387-38162-6 (Online)

3.     Debdeep Mukhopadhyay, Rajat Subhra Chakraborty, "Hardware Security: Design, Threats, and Safeguards," CRC Press 2015, ISBN 9781439895832

4.     Marc Joye, Michael Tunstall, "Fault Analysis in Cryptography," Springer 2012, ISBN: 978-3-642-29655-0 (Print) 978-3-642-29656-7 (Online)

Course Number

EC6212

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Network on Chip

Learning Mode

Lectures

Learning Objectives

Complies with Program Goals 1 and 2

Course Description

Network on Chip (NoC) refers to a scalable and efficient communication architecture for integrating multiple processing elements (PEs) or IP cores on a single semiconductor chip. The course typically covers topics such as NoC design principles, routing algorithms, arbitration mechanisms, and performance analysis for complex system-on-chip (SoC) designs.

Course Outline

Introduction to Network layers and Network Architecture; Network on Chip: System-on-Chip Integration and Its Challenges; SoC to Network-on-Chip: A Paradigm Shift;  NOC: Interconnection Networks, Architecture Design, Evaluation of Network-on-Chip Architectures, Application Mapping, Low-Power Techniques, Signal Integrity and Reliability, Testing, On-Chip multiprocessors; SoCs based NoCs: Examples;

Learning Outcomes

Complies with PLOs 1a, 1b, 2 and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1. Santanu Kundu, Santanu Chattopadhyay, “Network-on-Chip: The Next Generation of System-on-Chip Integration”, CRC press, 2014.

2. Jose Flich, Davide Bertozzi, “Designing Network On-Chip Architectures in the Nanoscale Era”, CRC press, 2010.

3. De Micheli & Benini, “Networks on Chips”, Elsevier, 2006

Course Number

EE5203

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Recent Trends in Optimization Techniques

Learning Mode

Lectures

Learning Objectives

Complies with Program goals 1 and 2

Course Description

The course is designed to meet the requirements of Ph.D. and M. Tech students to get sufficient knowledge on optimization and its application to different fields of engineering.

Course Outline

Motivation. mathematical review , matrix factorizations, sets and sequences, convex sets and functions.

Linear programming and simplex method, Weierstrass' theorem,

Karush Kuhn Tucker optimality conditions, algorithms, convergence, unconstrained optimization,

Line search methods, method of multidimensional search, steepest descent methods, Newton's method, modifications to Newton's method , trust region methods, conjugate gradient methods, quasi-Newton's methods.

Constrained optimization, penalty and barrier function methods, augmented Lagrangian methods, polynomial time algorithm for linear programming, successive linear programming, successive quadratic programming.

Learning Outcomes

Complies with PLO 1a, 2a, and 3a

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text/References

1.      R. Fletcher Practical Optimization (2nd Edition) John Wiley & Sons, New York, 1987.

2.      M.S.Bazaraa , H.D.Sherali and C.Shetty , Nonlinear Programming, Theory and Algorithms, John Wiley and Sons, New York, 1993.

Course Number

EE6214

Course Credit

L-T-P-C: 3-0-0-3

Course Title

Random Signals and Systems

Learning Mode

Lectures

Learning Objectives

Complies with Program Objectives 1 and 2.

Course Description

The course is designed to meet the requirements of Ph.D. and M. Tech students to get sufficient knowledge on random processes and its effects on linear systems.

Course Outline

Probability and statistics of multivariable (a quick revision): Bayes theorem, multiple random variable, discrete random variable, probability mass function and probability density function, a few well known distributions, moments.

Random process: Concept of random process, ensemble, mathematical tools for studying random process, correlation function, stationarity, ergodicity, a few known stochastic processes: random walk, Poisson process, Gaussian random process, Markov chains, Brownian motion etc., pseudorandom process, nonlinear transformation of random process.

Random process in frequency domain: Peridogram and power sprectral density, Weiner-Khintchine-Einstein Theorem, concept of bandwidth, spectral estimation.

Linear system: Discrete time and continuous time LTI system, concept of convolution, system described in frequency domain, state space description of the system.

Linear systems with random inputs: Linear system fundamentals, response of a linear system, convolution, mean, autocorrelation and cross correlation function in LTI system, power spectral density in LTI, cross power spectral density in LTI.

Processing of random signals: Noise in systems, noise bandwidth, SNR, bandlimited random process, noise reduction, matched filter, Wiener filter.

The Kalman filter: Mean square estimation, discrete Kalman filter, innovation, Kalman filter vs Wiener filter,properties of Kalman filter, Kalman Bucy filter, engineering examples.

Learning Outcomes

Complies with PLOs 1a, 2a, and 3a.

Assessment Method

Quizzes/Assignments, Mid Sem, and End Sem

Suggested Readings

Text

4.      Miller, Scott, and Donald Childers, “probability and random processes: with applications to signal processing and communications”, Academic Press, 2012.

5.      Wim C. van Etten, “Introduction to random signals and Noise”, Chichester, England: Wiley, 2005.

6.      Peyton Z. Peebles, “Probability, random variables, and random signal principles”. McGraw Hill Book Company, 1987.

References

1.       Geoffrey R. Grimmett, and David Stirzaker, “Probability and random processes”, Oxford university press, 2001.

2.      Alberto Leon-Garcia, “Probability, statistics, and random processes for Electrical engineering”, Upper Saddle River, NJ: Pearson/Prentice Hall, 2008.

3.      Grewal, Mohinder, and Angus P. Andrews, “Kalman filtering: theory and practice with MATLAB”, John Wiley & Sons, 2014.

4.      Alberto Leon-Garcia, “Probability, statistics, and random processes for Electrical engineering”, Upper Saddle River, NJ: Pearson/Prentice Hall, 2008.

5.      Kay, Steven M, “Fundamentals of statistical signal processing”, Prentice Hall PTR, 1993.

6.      H.L. Van Trees, “Detection, estimation, and modulation theory, part I”, New York, NY: John Wiley & Sons, Inc., 1971.

7.      Brown, Robert Grover, and Patrick YC Hwang., “Introduction to random signals and applied Kalman filtering”, New York: Wiley, 1992.

8.      Shovan Bhaumik, and Paresh Date, “Nonlinear estimation: methods and applications with deterministic Sample Points”, CRC Press, 2019.

9.      Steven Key, “Intuitive probability and random processes using MATLAB®”, Springer Science & Business Media, 2006.

10.  D. J. Gordana, “Random signals and processes primer with MATLAB”, Springer Science & Business Media, 2012