Electronics & Comm. Eng. — 6th Semester Syllabus

1. MOS transistor theory and modelling (8 Hours)

The Metal Oxide Semiconductor (MOS) Structure • MOS System under External Bias • Structure and Operation of MOS Transistor (MOSFET) • Current-Voltage Characteristics • Scaling and Small-geometry Effects • MOSFET modelling • Small-signal model

2. Fabrication and Layout of CMOS ICS (8 Hours)

Fabrication Process Flow: Basic Steps • CMOS Well Process • Layout Design Rules • Full-Custom Mask Layout Design

3. MOS INVERTERS (10 Hours)

Static characteristics: Resistive-Load Inverter, Inverters with n-Type MOSFET Load, CMOS Inverter • Switching characteristics and interconnect effects: Delay-Time definitions, Calculation of Delay times, Inverter Design with Delay Constraints • Estimation of Interconnect Parasitics, Calculation of Interconnect Delay • Switching Power Dissipation of CMOS Inverters

4. Combinational MOS logic circuits (8 Hours)

MOS Logic Circuits with Depletion nMOS Loads • CMOS Logic Circuits • Complex Logic Circuits • CMOS Transmission Gates (Pass Gates)

5. Sequential MOS logic circuits (8 Hours)

Behaviour of Bistable elements • The SR Latch Circuit • Clocked Latch and Flip-Flop Circuits • CMOS D-Latch and Edge-Triggered Flip-Flop

1. Digital Image Fundamentals

Elements of visual perception • Image sensing and acquisition • Image sampling and quantization • Basic relationships between pixels – neighborhood, adjacency, connectivity, distance measures

2. Image Enhancements and Filtering

Gray level transformations • Histogram equalization and specifications • Pixel-domain smoothing filters – linear and order-statistics • Pixel-domain sharpening filters – first and second derivative • Two-dimensional DFT and its inverse • Frequency domain filters – low-pass and high-pass

3. Color Image Processing

Color models–RGB, YUV, HSI • Color transformations– formulation, color complements, color slicing, tone and color corrections • Color image smoothing and sharpening • Color Segmentation

4. Image Segmentation

Detection of discontinuities • Edge linking and boundary detection • Thresholding– global and adaptive • Region-based segmentation

5. Wavelets and Multi-resolution image processing

Uncertainty principles of Fourier Transform • Time frequency localization • Continuous wavelet transforms • Wavelet bases and multi-resolution analysis • Wavelets and Subband filter banks, wavelet packets • Image Compression: Redundancy–inter-pixel and psycho-visual; Lossless compression – predictive, entropy; Lossy compression predictive and transform coding; Discrete Cosine Transform; Still image compression standards–JPEG and JPEG-2000

6. Fundamentals of Video Coding

Inter-frame redundancy • Motion estimation techniques – full-search, fast search strategies, forward and backward motion prediction • Frame classification – I, P and B • Video sequence hierarchy–Group of pictures, frames, slices, macro-blocks and blocks • Elements of a video encoder and decoder • Video coding standards – MPEG and H.26X • Video Segmentation: Temporal segmentation–shot boundary detection, hard cuts and soft-cuts; spatial segmentation–motion-based; Video object detection and tracking

1. Introduction

Sources of Approximations • Data Error and Computational • Truncation Error and Rounding Error • Absolute Error and Relative Error • Sensitivity and Conditioning • Backward Error Analysis • Stability and Accuracy • Computer Arithmetic: Floating Point Numbers, Normalization, Properties of Floating Point System, Rounding, Machine Precision, Subnormal and Gradual Underflow, Exceptional Values, Floating-Point Arithmetic, Cancellation

2. System of Linear Equations

Linear Systems, Solving Linear Systems • Gaussian elimination, Pivoting, Gauss-Jordan • Norms and Condition Numbers • Symmetric Positive Definite Systems and Indefinite System • Iterative Methods for Linear Systems • Linear least squares: Data Fitting, Linear Least Squares, Normal Equations Method, Orthogonalization Methods, QR factorization, Gram-Schmidt Orthogonalization, Rank Deficiency, and Column Pivoting

3. Eigenvalues, Singular Values, Nonlinear Equations, and Optimization

Eigenvalues and singular values: Eigenvalues and Eigenvectors, Methods for Computing All Eigenvalues, Jacobi Method, Methods for Computing Selected Eigenvalues, Singular Values Decomposition, Application of SVD • Nonlinear equations: Fixed Point Iteration, Newton's Method, Inverse Interpolation Method • Optimization: One-Dimensional Optimization, Multidimensional Unconstrained Optimization, Nonlinear Least Squares

4. Interpolation, Numerical Integration, and Differential Equations

Interpolation: Purpose for Interpolation, Choice of Interpolating Function, Polynomial Interpolation, Piecewise Polynomial Interpolation • Numerical Integration And Differentiation: Quadrature Rule, Newton-Cotes Rule, Gaussian Quadrature Rule, Finite Difference Approximation • Initial Value Problems for ODEs: Euler's Method, Taylor Series Method, Runga-Kutta Method, Extrapolation Methods • Boundary Value Problems For ODEs: Finite Difference Methods, Finite Element Method, Eigenvalue Problems

5. Advanced Topics

Partial Differential Equations: Time Dependent Problems, Time Independent Problems, Solution for Sparse Linear Systems, Iterative Methods • Fast Fourier Transform: FFT Algorithm, Limitations, DFT, Fast polynomial Multiplication • Wavelets • Random Numbers And Simulation: Stochastic Simulation, Random Number Generators, Quasi-Random Sequences