I SEMESTER LINEAR ALGEBRA Subject Codevtu.ac.in/pdf/pg2012/lspsyll.pdf · I SEMESTER LINEAR ALGEBRA Subject Code : ... Array fundamentals, ... Multichip module packaging and Wafer

1

I SEMESTER

LINEAR ALGEBRA

Subject Code : 12EC046 IA Marks : 50 No. of Lecture Hours /week : 04 Exam Hours : 03 Total no. of Lecture Hours : 52 Exam Marks : 100

Linear Equations: Fields; system of linear equations, and its solution sets; elementary row operations and echelon forms; matrix operations; invertible matrices, LU-factorization. (Ref.2 Chap.1) Vector Spaces: Vector spaces; subspaces; bases and dimension; coordinates; summary of row-equivalence; computations concerning subspaces. (Ref.1 Chap.2) Linear Transformations: Linear transformations; algebra of linear transformations; isomorphism; representation of transformations by matrices; linear functionals; transpose of a linear transformation. (Ref.2 Chap.3) Canonical Forms: Characteristic values; annihilating polynomials; invariant subspaces; direct-sum decompositions; invariant direct sums; primary decomposition theorem; cyclic bases; Jordan canonical form. Iterative estimates of characteristic values. (Ref.2 Chap.6) Inner Product Spaces: Inner products; inner product spaces; orthogonal sets and projections; Gram-Schmidt process; QR-factorization; least-squares problems; unitary operators. (Ref.1 Chap.8) Symmetric Matrices and Quadratic Forms: Digitalization; quadratic forms; constrained optimization; singular value decomposition. (Ref.2 Chap.7) REFERENCE BOOKS:

1.David. C. Lay, “Linear Algebra and its Applications,” 3rd edition,

Pearson Education (Asia) Pte. Ltd, 2005.

2.Kenneth Hoffman and Ray Kunze, "Linear Algebra ," 2nd edition,

Pearson Education (Asia) Pte. Ltd/ Prentice Hall of India, 2004. .

3.Bernard Kolman and David R. Hill, "Introductory Linear Algebra

with Applications," Pearson Education (Asia) Pte. Ltd, 7th edition, 2003.

2

4.Gilbert Strang, "Linear Algebra and its Applications," 3rd edition,

Thomson Learning Asia, 2003.

STATISTICAL SIGNAL PROCESSING


Random Processes: Random variables, random processes, white noise, filtering random processes, spectral factorization, ARMA, AR and MA processes. (Ref.1 Chap.3) Signal Modeling: Least squares method, Padé approximation, Prony's method, finite data records, stochastic models, Levinson-Durbin recursion; Schur recursion; Levinson recursion. (Ref.1 Chap.4 & 5) Spectrum Estimation: Nonparametric methods, minimum-variance spectrum estimation, maximum entropy method, parametric methods, frequency estimation, principal components spectrum estimation.(Ref.1 Chap.8) Optimal and Adaptive Filtering: FIR and IIR Wiener filters, Discrete Kalman filter, FIR Adaptive filters: Steepest descent, LMS, LMS-based algorithms, adaptive recursive filters, RLS algorithm. (Ref.1 Chap.7 & 9) Array Processing: Array fundamentals, beam-forming, optimum array processing, performance considerations, adaptive beam-forming, linearly constrained minimum-variance beam-formers, side-lobe cancellers, space-time adaptive processing. (Ref.2 Chap.11) REFERENCE BOOKS:

1.Monson H. Hayes, “Statistical Digital Signal Processing and

Modeling”, John Wiley & Sons (Asia) Pte. Ltd., 2002.

2.Dimitris G. Manolakis, Vinay K. Ingle, and Stephen M. Kogon,

"Statistical and Adaptive Signal Processing: Spectral Estimation,

Signal Modeling, Adaptive Filtering and Array Processing”,

McGraw-Hill International Edition, 2000.

3

3.Bernard Widrow and Samuel D. Stearns, "Adaptive Signal

Processing”, Pearson Education (Asia) Pte. Ltd., 2001.

4.Simon Haykin, "Adaptive Filters” , Pearson Education (Asia) Pte. Ltd,

4th edition, 2002.

5.J.G. Proakis, C.M. Rader, F. Ling, C.L. Nikias, M. Moonen and I.K.

Proudler, "Algorithms for Statistical Signal Processing," Pearson

Education (Asia) Pte. Ltd, 2002.

AUDIO AND SPEECH PROCESSING


INTRODUCTION: The speech signal, signal processing, digital signal processing, digital speech processing, digital transmission and storage of speech, speech synthesis systems, speaker verification and identification, speech recognition systems, aids-to-the-handicapped, enhancement of signal quality (Ref.1 Chap.1) Digital Models for the Speech Signal: Process of speech production, the mechanism of speech production. (Ref.1 Chap.3) Time Domain Models For Speech Processing: Time dependent processing of speech, Short time energy and average magnitude, Short time average zero crossing rate, Speech vs silence discrimination using energy & zero crossings. (Ref.1 Chap.4) Digital Representations of the Speech Waveform: Sampling speech signals, Review of statistical model for speech, Instantaneous quantization, Uniform quantization, Instantaneous companding, quantization for optimum SNR (Ref.1 Chap.5) Short Time Fourier Analysis: Definitions and properties, Fourer transform interpretation, Linear Filtering interpretation, sampling rates, time and frequency, Filter bank summation method, Short time synthesis, Overlap addition method, short time synthesis (Ref.1 Chap.6)

4

Linear Predictive Coding of Speech: Basic principles of linear predictive analysis, autocorrelation method, covariance method, computation of gain (Ref.1 Chap.8) Digital speech processing for man-machine communication by voice: Voice response systems, general considerations in the design of voice response systems, multiple output digital voice response systems, speech synthesis by concatenation of formant coded words, typical applications of computer voice response systems, speaker recognition systems, speaker verification systems, speaker identification systems (Ref.1 Chap.9) Audio Processing: Basics of digital audio, digitization of sound, Nyquist theorem, signal to noise ratio, signal to quantization noise ratio, linear and nonlinear quantization, audio filtering, audio quality vs. data rate, synthetic sounds, MIDI, MIDI overview, hardware aspects of MIDI, structure of MIDI messages, general MIDI, MIDI to WAV conversion, quantization and transmission of audio, coding of audio, pulse code modulation, differential coding of audio, lossless predictive coding, DPCM, DM, ADPCM. (Ref.2 Chap.6)

REFERENCE BOOKS: 1.L. R. Rabiner and R. W. Schafer, “Digital Processing of Speech Signals”,

Pearson Education (Asia) Pte. Ltd., 2004.

2.Z. Li and M.S. Drew, “Fundamentals of Multimedia”, Pearson Education

(Asia) Pte. Ltd., 2004

DSP ALGORITHMS & ARCHITECTURE


Introduction : Reviews of various DSP Algorithms and their representation using block diagrams, signal flow graphs, and data flow graphs, iteration bound. (Ref.1 Chap.1.& 2)

Pipelining and parallel processing. Introduction pipelinig of FIR digital filters, parallel processing for low power, problems (Ref.1 Chap.3.)

5

Retiming, Unfolding and folding techniques: Introduction, Definitions, properties, applications, problems. (Ref.1 Chap.4, 5.& 6)

Systolic Architecture design: Methodology, FIR systolic arrays, selection and design for space representations containing delays, problems (Ref.1 Chap.7)

Fast convolution: Introduction Cook-Toom and winograd convolution algorithms: Introduction, Iterated convolution, cyclic convolution, design of fast convolution algorithm by inspection, problems (Ref.1 Chap. 8)

Algorithmic Strength Reduction in Filters and Transforms: Introduction, parallel FIR filters, DCT, parallel architectures for rank order filters. (Ref.1 Chap.9.)

Pipelined and Parallel Recursive and adaptive filters: Introduction, pipeline interleaving in digital filters, pipeling in first order IIR digital filters, Parallel processing for IIR filters, Low power IIR filter design, pipelined adaptive Digital filters. (Ref.1 Chap.10.)

Bit level Arithmetic Architectures: Parallel multipliers bit serial multipliers, distributed arithmetic, Redundant Arithmetic- Redundant number representation, data format conversion, Numerical Strength reduction- Multiple constant multipilaction, additive and multiplicative number splitting. (Ref.1 Chap.13, 14. & 15)

REFERENE BOOKS:

1. 1. Keshab K Parhi, “VLSI Digital Signal Processing Systems”, Jhon Wiley and Son’s, India,2011.

2. Peter Prissch, “Architecutres for Digital Signal Processing “, Jhon Wiley and Son’s, New York, 1999 ELECTIVE - I

CAD FOR SIGNAL PROCESSING

6


Digital Signal Processing of Continues Time Signals: Sampling process in time Domain, effect of sampling in frequency domain. Among low pass filter. A to D and D to A conversions. (Ref.1 Chap 5) Realization of FIR, IIR filter, Design of digital filter and simulation of IIR, FIR filters. (Ref.1Chap 6 & 7) Multirate Digital Signal Processing: Sampling rate alteration, devices, decimator and Interpolator, design and implementation. Design of filter banks, design of Nyquist filters, (Ref.1Chap 10) Application of DSP using Mat lab by Sanjitmitra, Computer Based approach; (Ref.1Chap 14) Application In Communication and Adaptive Filtering : LMS algorithms, system identifications, suppression of narrow band interference in a mid band signal. (Ref.3Chap 9) Adaptive line enhancement, Adaptive channel equalization. PCM, DPCM, DM of speech binary digital communication. Spread spectrum communication. (Ref.3, Chap 10) Digital Image processing, the origins of Digital Image Processing, Fundamental Steps in Digital Image processing, (Ref.4 Chap 1) Digital Image Fundamentals, Elements of Visual Perception, Light and the electromagnetic spectrum, Image Sensing and Acquisition, Image Sampling and quantization, (Ref.4 Chap 2) REFERENCE BOOKS:

1.Sanju K Mitra, “Digital Signal Laboratory using Mat Lab” , MGH

Ed. 2000

2.William H Trantra, K. Shanmugam, Theodore S. Rappaport, Kurt L.

Kosbar, “Principles of communication systems simulation with

wireless applications”, Pearson Edn, 2004

7

3.Vinay K Ingle and Jhon G Proakis, “Digital Processing using Mat

Lab”, Thomson, Indian Ed., 2003

4.R. C. Gonzalez, Richard E Woods, Steven L. Eddma, “Digital Image

Processing”, Pearson Educatuion, Edn. 2004

5.Digital Signal Processing : - A Computer Based Approach – Sanjit K

Mitra

, RF MEMS


Review – Introduction to MEMS. Fabrication for MEMS, MEMS transducers and Actuators . Microsensing for MEMS, Materials for MEMS.(Ref.1, Chap.1) MEMS materials and fabrication techniques – Metals, Semiconductors, thin films, Materials for Polymer MEMS, Bulk Machining for silicon based MEMS, Surface machining for Silicon based MEMS, Micro Stereo Lithography for Polymer MEMS. (Ref.1, Chap.2) RF MEMS Switches and micro – relays. Switch Parameters, Basics of Switching, Switches for RF and microwave Applications , Actuation mechanisms, micro relays and micro actuators, Dynamics of Switch operation, MEMS Switch Design and design considerations. MEMS Inductors and capacitors.(Ref.1, Chap.3 & 4) Micromachined RF Filters and Phase shifters. RF Filters, Modeling of Mechanical Filters, Micromachanical Filters, SAW filters – Basics, Design considerations. Bulk Acoustic Wave Filters, Micromachined Filters for Millimeter Wave frequencies. Micromacbined Phase Shifters, Types and Limitations, MEMS and Ferroelectric Phase shifters, Applications. (Ref.1, Chap.5 & 6)

8

Micromachined transmission lines and components. Micromachined Transmission Lines – Losses in Transmission lines, coplanar lines, Meicroshield and membrane supported lines, Microshield components, Micromachined waveguides, directional couplers and mixers, Resonators and Filters. (Ref.1, Chap.7) Micomachined antennas. Design, Fabrication and Measurements. Integration and Packaging for RF MEMS. Roles and types of Packages, Flip Chip Techniques, Multichip module packaging and Wafer bonding, Reliability issues and Thermal issues. (Ref.1, Chap.8 & 9) References Books :

1RF MEMS – V K Varadan, A Laktakia and K J Vinoy, John Wiley, 2003 Reprint 2.RF MEMS Circuit Design J De Los Santos, Artech House, 2002. 3.Transaction Level Modeling with SystemC: TLM Concepts and Applications for Embedded Systems, by Frank Ghenassia, Springer, 2005. 4.Networks on Chips: Technology and Tools, by Luca Benini and Giovanni De Micheli , Morgan Kaufmann Publishers, 2006.

BIO-MEDICAL SIGNAL PROCESSING


INTRODUCTION : Characteristics of medical data, medical instruments,Evoluation of microprocessor based systems, the microcomputer based medical instrument, software design of digital filters (Ref.1 Chap.1) ECG: Basic ECG, lead systems, signal characteristics, analog filters, amplifiers and QRS detectors. (Ref.1 Chap.2) Adaptive Filters and Signal Averaging : noise canceler model, 60-Hz adaptive canceling, other applications , Basics signal averaging, a digital filter, averager, software for signal averaging, limitations. (Ref.1 Chap. 8 & 9)

9

Data Reduction Techniques: Turning point algorithm, AZTEC algorithm, Fan algorithm, Huffman coding. (Ref.1 Chap.10) ECG QRS Detection and analysis: Power spectrum of the ECG, Bandpass filtering, differentiation, template matching techniques, ECG interpretation, ST-segment analyser, portable arrhythmia monitor. (Ref.1 Chap.12 & 13) EEG: evoked responses, Epilepsy detection, Spike detection, Hjorth parameters, averaging techniques, removal of Artifacts by averaging and adaptive algorithms, pattern recognition of alpha, beta, theta and delta waves in EEG waves, sleep stages, (Ref.2 Chap.6 & 7) EMG: wave pattern studies, biofeedback, Zero crossings, Integrated EMG. Time frequency methods and Wavelets in Biomedical Signal Processing (Ref.2 Chap.10 & 11) REFERENCE BOOKS:

1. Willis J Tompkins, ED. “Biomedical Digital Signal Processing”, C- Language examples , Prentice-Hall of India, 2006.

2. Willis J Tompkins, ED. “Biomedical Digital Signal Processing”, Prentice-Hall of India, 1996.

3. R E Chellis and R I Kitney, “Biomedical Signal Processing”, in IV parts, Medical and Biological Engg. And current computing, 1990-91. 4. Special issue on Biological Signal Processing, Proc. IEEE 1972 5. Arnon Kohen, “Biomedical Signal Processing”, Volumes I & II,

CRC Press. 6. Metin Aray, “Time frequency and Wavelets in Biomedical Signal Processing”, IEEE Press, 1999. Current Published literature.

II – SEMESTER

DIGITAL SIGNAL COMPRESSION


Introduction: Compression techniques, Modeling & coding, Distortion criteria, Differential Entropy, Rate Distortion Theory, Vector Spaces,

10

Information theory, Models for sources, Coding – uniquely decodable codes, Prefix codes, Kraft McMillan Inequality (Ref.1 Chap.1 & 2.) Quantization: Quantization problem, Uniform Quantizer, Adaptive Quantization, Non-uniform Quantization; Entropy coded Quantization, Vector Quantization, LBG algorithm, Tree structured VQ, Structured VQ, Variations of VQ – Gain shape VQ, Mean removed VQ, Classified VQ, Multistage VQ, Adaptive VQ, Trellis coded quantization(Ref.1 Chap.9 &10) Differential Encoding: Basic algorithm, Prediction in DPCM, Adaptive DPCM, Delta Modulation, Speech coding – G.726, Image coding.(Ref.1 Chap. 11 Transform Coding: Transforms – KLT, DCT, DST, DWHT; Quantization and coding of transform coefficients, Application to Image compression – JPEG, Application to audio compression. (Ref.4 Chap. 13) Sub-band Coding: Filters, Sub-band coding algorithm, Design of filter banks, Perfect reconstruction using two channel filter banks, M-band QMF filter banks, Poly-phase decomposition, Bit allocation, Speech coding – G.722, Audio coding – MPEG audio, Image compression. (Ref.1 Chap. 14) Wavelet Based Compression: Wavelets, Multiresolution analysis & scaling function, Implementation using filters, Image compression – EZW, SPIHT, JPEG 2000. (Ref.4 Chap. 8) Analysis/Synthesis Schemes: Speech compression – LPC-10, CELP, MELP, Image Compression – Fractal compression. (Ref.1 Chap. 17) Video Compression: Motion compensation, Video signal representation, Algorithms for video conferencing & videophones – H.261, H. 263, Asymmetric applications – MPEG 1, MPEG 2, MPEG 4, MPEG 7, Packet video. (Ref.4 Chap. 10,11, 12) Lossless Coding: Huffman coding, Adaptive Huffman coding, Golomb codes, Rice codes, Tunstall codes, Applications of Huffman coding, Arithmetic coding, Algorithm implementation, Applications of Arithmetic coding, Dictionary techniques – LZ77, LZ78, Applications of LZ78 – JBIG, JBIG2, Predictive coding – Prediction with partial match, Burrows Wheeler Transform, Applications – CALIC, JPEG-LS, Facsimile coding – T.4, T.6.(Ref.4 Chap. 7)

11

REFERENCE BOOKS:

1.K. Sayood, “ Introduction to Data Compression," Harcourt India Pvt.

Ltd. & Morgan Kaufmann Publishers, 1996.

2.N. Jayant and P. Noll, “Digital Coding of Waveforms: Principles

and Applications to Speech and Video,” Prentice Hall, USA, 1984.

3.D. Salomon, “Data Compression: The Complete Reference”,

Springer, 2000.

4.Z. Li and M.S. Drew, “Fundamentals of Multimedia,” Pearson

Education (Asia) Pte. Ltd., 2004.

MODERN DSP Subject Code : 12EC123 IA Marks : 50

No. of Lecture Hours/Week : 04 Exam Marks : 03

Total No. of Lecture Hours : 52 Exam Hours : 100

Goal of the course – Advances in Digital Signal Processing involve variable sampling rates and thus the multirate signal processing and hence their applications in communication systems and signal processing. It is intended to introduce a basic course in multirate signal processing especially meant for students of branches eligible for M Tech courses in EC related disciplines.

Introduction and Discrete Fourier Transforms: Signals, Systems and Processing, Classification of Signals, The Concept of Frequency in Continuous-Time and Discrete-Time Signals, Analog-to-Digital and Digital-to-Analog Conversion, Frequency-Domain Sampling: The Discrete Fourier Transform, Properties of the DFT, Linear Filtering Methods Based on the DFT(Ref.1 Chap. 1 & 7)

Design of Digital Filters: General Considerations, Design of FIR Filters, Design of IIR Filters from Analog Filters, Frequency Transformations.(Ref.1 Chap. 10)

Multirate Digital Signal Processing: Introduction, Decimation by a factor ‘D’, Interpolation by a factor ‘I’, Sampling rate Conversion by a factor ‘I/D’, implementation of Sampling rate conversion, Multistage implementation of

12

Sampling rate conversion, Sampling rate conversion of Band Pass Signals, Sampling rate conversion by an arbitrary factor, Applications of Multirate Signal Processing, Digital Filter banks, Two Channel Quadrature Mirror Filter banks, M-Channel QMF bank.(Ref.1 Chap. 11)

Adaptive Filters: Applications of Adaptive Filters, Adaptive Direct Form FIR Filters- The LMS Algorithm, Adaptive Direct Form Filters-RLS Algorithm. (Ref.1 Chap. 13)

References:

1. Proakis and Manolakis, “Digital Signal Processing”, Prentice Hall 1996. (third edition).

2. Roberto Cristi, “Modern Digital Signal Processing”, Cengage Publishers, India, (erstwhile Thompson Publications), 2003.

3. S.K. Mitra, “Digital Signal Processing: A Computer Based Approach” , III Ed, Tata McGraw Hill, India, 2007.

4. E.C. Ifeachor and B W Jarvis, “Digital Signal Processing, a practitioners approach,” II Edition, Pearson Education, India, 2002 Reprint.

MODERN SPECTRAL ANALYSIS & ESTIMATION


Basic Concepts: Introduction, Energy Spectral Density of deterministic signals, Power Spectral Density of random signals, properties of Power Spectral Densities, The Spectral Estimatuion problem, Coherence Spectrum. (Ref.1 Chap.1) Spectrum Estimation: Introduction, Correlogram method, Periodogram Computation Via FFT, properties of Periodogram method such as bias analysis, window design considerations. Signals with Rational spectra. ARMA state – space Equation, sub space Parameter Estimation.(Ref.1 Chap.2) Parametric Methods for line Spectra: Models of sinusoidal Signals in Noise, Non-linear least squares method. High Order Yule Walker method, Min – Norm Method, ESPRIT Method, Forward – Backward Estimatuion.(Ref.1 Chap.4)

13

Filter Bank Method : Filter bank Interpretation of the period gram, Refined Filter bank Method, Capon Method, Filter Bank Reinterpretation of the periodogram.(Ref.1 Chap.5) Optimum Linear Filter : Optimum Signal Estimation, Linear MSE Estimation, Solution of the normal equations optimum FIR and IIR filters. Inverse filtering and deconvolution.(Ref.2 Chap.6) REFERENCE BOOKS:

1.Stoica and Moses, “Introduction to Spectral Analysis”, PHI, 1997.

2.Monalakis, Ingle and Kogen, “Stastical and Adaptive Signal

Procedssing”, Tata McGraw Hill. 2000.

REAL TIME DIGITAL SIGNAL PROCESSING


Introduction to Digital Signal Processing System: Introduction, DSP systems and Applications, Architectures, Software developments, Hardware issues, system considerations. (Ref.1: Chap.1) Implementation Considerations: Introduction, Data Representation & Arithmetic’s, finite word length effects, Programming issues, Real-time implementation considerations, Hardware interfacing. (Ref.1 Chap.3) Fixed point Digital signal processors: Introduction, TMS320C54x, Architecture overview and Instruction sets, Problems. (Ref.1Chap .4) Floating point Digital Signal processor: Introduction, TMS320C67x Architecture overview and Instruction sets, Problems. (Ref.1 Chap.5) Finite impulse response filtering: Introduction, Design of FIR filters using MAT lab, Fixed and floating point implementations and applications, Problems. (Ref.1 Chap.6)

14

Infinite impulse response filtering: Introduction, Design of IIR filters using MAT lab, Fixed and floating point implementations and applications, Problems (Ref.1 Chap.7)

Fast Fourier transform: Introduction to DFT, FFT algorithms, Analysis and implementation using MAT Lab, Implementation considerations, Fixed and floating point implementations and applications, Problems (Ref.1 Chap.8)

Adaptive filtering: Introduction, Filter Structure and Algorithms Properties, Applications, Design and Implementations using MAT Lab, Fixed and floating point implementations and applications, Problems (Ref.1: Chap.9)

REFRENCE BOOKS: 1. Sen M Kuo & Woon-Seng S. Gan “Digital Signal Processing” Pearson, 2011

2. Nasser Kehtarnavaz “Real-Time Digital Signal Processin Based on the TMS320C6000” Elsevier, 2005

3. Rulph Chassing “DSP Application Using C and the TMS320C6x DSK” John Wiley and son’s New York,2002

ELECTIVE II

DETECTION AND ESTIMATION


Classical Detection and Estimation Theory: Introduction, simple binary hypothesis tests, M Hypotheses, estimation theory, composite hypotheses, general Gaussian problem, performance bounds and approximations. (Ref.1 Chap. 2) Representations of Random Processes: Introduction, orthogonal representations, random process characterization, homogenous integral equations and eigen-functions, periodic processes, spectral decomposition,

15

vector random processes. (Ref.1 Chap. 3) Detection of Signals – Estimation of Signal Parameters: Introduction, detection and estimation in white Gaussian noise, detection and estimation in nonwhite Gaussian noise, signals with unwanted parameters, multiple channels and multiple parameter estimation. (Ref.1 Chap. 4) Estimation of Continuous Waveforms: Introduction, derivation of estimator equations, a lower bound on the mean-square estimation error, multidimensional waveform estimation, nonrandom waveform estimation. (Ref.1 Chap. 5) Linear Estimation: Properties of optimum processors, realizable linear filters, Kalman-Bucy filters, fundamental role of optimum linear filters. (Ref.1 Chap. 6) REFERENCE BOOKS:

1.Harry L. Van Trees, “Detection, Estimation, and Modulation

Theory” , Part I, John Wiley & Sons, USA, 2001.

2.M.D. Srinath, P.K. Rajasekaran and R. Viswanathan, "Introduction to

Statistical Signal Processing with Applications,” Pearson Education

(Asia) Pte. Ltd. /Prentice Hall of India, 2003.

3.Steven M. Kay, "Fundamentals of Statistical Signal Processing,"

Volume I: "Estimation Theory", Prentice Hall, USA, 1998;

4.Steven M. Kay, "Fundamentals of Statistical Signal Processing,

"Volume II: "Detection Theory” , Prentice Hall, USA, 1998.

5.K Sam Shanmugam, Arthur M Breipohl, “Random Signals:

Detection, Estimation and Data Analysis”, John Wiley & Sons, 1998

WIRELESS COMMUNICATIONS


16

Wireless channel: physical modeling for wireless channels, input/output model of wireless channel, time and frequency response, statistical models. (Ref.1 Chap. 2)

Point to point communication: detection in rayleigh fading channel, time diversity, antenna diversity, frequency diversity, impact of channel uncertainity.(Ref.1 Chap. 3)

Diversity: Introduction, Microdiversity, Microdiversity and simulcast, Combination of Signals, Error Probability in fading channels with diversity Reception, transmit diversity. (Ref.2 Chap. 13)

Capacity of wireless channels: AWGN channel capacity, resources of AWGN channel, Linear time invariant gaussian channels, capacity of fading channels. (Ref.1 Chap. 5)

MIMO Systems: Introduction, Space Diversity and Systems Based on Space Diversity, Smart antenna system and MIMO, MIMO based System architecture, MIMO exploits multipath, Space time Processing, Antenna considerations for MIMO, MIMO channel Modeling, MIMO Channel measurement, MIMO Channel capacity, CDD, Space Time Coding, Advantages and Applications of MIMO, MIMO applications in 3G (Ref.4 Chap. 15)

MIMO 1 – Spatial multiplexing and channel modeling: multiplexing capability of MIMO channels, physical modeling of MIMO channels, modeling MIMO fading channels. (Ref.1 Chap. 7)

Multi Antennae Systems: Smart antennas, Multiple Input Multiple Output Systems, (Ref.1 Chap. 20)

References Books:

1. David Tse, P. Viswanath, “Fundamentals of wireless communication”, Cambridge, 2006.

2. Andreas Molisch, “Wireless communications”, Wiley, 2009

3.William C Y Lee, “Mobile Communication Engineering Theory and applications”, TMGH, 2008

4. Upen Dalal, “Wireless communication”, Oxford, 2009

5. Mark Ciampa, Jorge Olenwa, “Wireless communications”, Cengage, 2007.

MEDICAL IMAGING

17


A number of new, imaging techniques and modalities in imaging area have revolutionized the Medicare In this Course principles of various imaging modalities are to be discussed (Ref.1 Chap.1) X-Rays: X ray diagnostjc methods, Conventional x-ray radiography fluoroscopy and angiography computed tomography: Recent developments in x-ray unit characteristics. Biological effects ionizing radiation (Ref.1 Chap.1) Computed Tomography: Basic principles, system components and truncations of scanning systems, Medical applications and safety precautions, Discussion on reconstruction algorithms (Ref.1 Chap.1) Ultrasound:. Functional block diagram of basic pulse echo system for diagnostic purposes, A mode, B mode and M mode principles of echocardiography (Ref.1 Chap.2) Radio Nuclide Imaging: Principles, schematic functional diagram and components of gamma, Medical applications, safety precautions. (Ref.1 Chap.3) Magnetic Resonance Imaging: Basic principles, Signals excitation and detection, Schematic functional diagram of MRI scanner with its sub systems, Magnet gradient systems, RF transmitter- receiver system, medical applications, safety precautions. (Ref.1 Chap.4) REFERENCE BOOKS:

1.Kirk Shung, Michael B, Smith, Benjamin M W Tsui, “Principles of medical imaging”, Academic press

2.Zhong Hicho and Manbir Singh “Fundamentals of Medical imaging” John Wiley, 1993

3.Peter Josefell &Edward Sudney “Nuclear Medicine introductory Text”, William Blackwell Scientific Publishers London

18

4.G.T. Herman, “Imaging reconstruction from projections — Implementation and applications”, Topics in applied physics vol.32 Springer Verlag’ 1979.

III – SEMESTER

IMAGE AND VIDEO PROCESSING


Introduction: 2D systems, Mathematical preliminaries – Fourier Transform, Z Transform, Optical & Modulation transfer function, Matrix theory, Random signals, Discrete Random fields, Spectral density function.(Ref.1, Chap.2) Image Perception: Light, Luminance, Brightness, Contrast, MTF of the visual system, Visibility function, Monochrome vision models, Fidelity criteria, Color representation, Chromaticity diagram, Color coordinate systems, Color difference measures, Color vision model, Temporal properties of vision.(Ref.1, Chap.3) Image Sampling and Quantization: Introduction, 2D sampling theory, Limitations in sampling & reconstruction, Quantization, Optimal quantizer, Compander, Visual quantization.(Ref.1, Chap.4) Image Transforms: Introduction, 2D orthogonal & unitary transforms, Properties of unitary transforms, DFT, DCT, DST, Hadamard, Haar, Slant, KLT, SVD transform.(Ref.1, Chap.5) Image Representation by Stochastic Models: Introduction, one-dimensional Causal models, AR models, Non-causal representations, linear prediction in two dimensions. (Ref.1, Chap.6) Image Enhancement: Point operations, Histogram modeling, spatial operations, Transform operations, Multi-spectral image enhancement, false

19

color and Pseudo-color, Color Image enhancement.(Ref.1, Chap.7) Image Filtering & Restoration: Image observation models, Inverse & Wiener filtering, Fourier Domain filters, Smoothing splines and interpolation, Least squares filters, generalized inverse, SVD and Iterative methods, Maximum entropy restoration, Bayesian methods, Coordinate transformation & geometric correction, Blind de-convolution. (Ref.1, Chap.8) Image Analysis & Computer Vision: Spatial feature extraction, Transform features, Edge detection, Boundary Extraction, Boundary representation, Region representation, Moment representation, Structure, Shape features, Texture, Scene matching & detection, Image segmentation, Classification Techniques.(Ref.1, Chap.9) Image Reconstruction from Projections: Introduction, Radon Transform, Back projection operator, Projection theorem, Inverse Radon transform, Fourier reconstruction, Fan beam reconstruction, 3D tomography(Ref.1, Chap.10) . Image Data Compression: Introduction, Pixel coding, Predictive techniques, Transform coding, Inter-frame coding, coding of two tone images, Image compression standards. (Ref.1, Chap.11) Video Processing: Fundamental Concepts in Video – Types of video signals, Analog video, Digital video, Color models in video, Video Compression Techniques – Motion compensation, Search for motion vectors, H.261, H.263, MPEG I, MPEG 2, MPEG 4, MPEG 7 and beyond, Content based video indexing. Ref. 4. REFERENCE BOOKS:

1.K. Jain, “Fundamentals of Digital Image Processing," Pearson

Education (Asia) Pte. Ltd./Prentice Hall of India, 2004.

2.Z. Li and M.S. Drew, “Fundamentals of Multimedia,” Pearson

Education (Asia) Pte. Ltd., 2004.

3.R. C. Gonzalez and R. E. Woods, “Digital Image Processing,” 2nd

edition, Pearson Education (Asia) Pte. Ltd/Prentice Hall of India, 2004.

4. M. Tekalp, “Digital Video Processing,” Prentice Hall, USA, 1995.

20

ELECTIVE - III PATTERN RECOGNITION


Introduction: Applications of pattern recognition, statistical decision theory, image processing and analysis.(Ref.1, Chap.1) Probability: Introduction, probability of events, random variables, Joint distributions and densities, moments of random variables, estimation of parameters from samples, minimum risk estimators(Ref.1, Chap.2) Statistical Decision Making: Introduction, Baye’s Theorem, multiple features, conditionally independent features, decision boundaries, unequal costs of error, estimation of error rates, the leaving-one—out technique. Characteristic curves, estimating the composition of populations. (Ref.1, Chap.3) Nonparametric Decision Making: Introduction, histograms, Kernel and window estimators, nearest neighbor classification techniques, adaptive decision boundaries, adaptive discriminate Functions, minimum squared error discriminate functions, choosing a decision making technique. (Ref.1, Chap.4) Clustering: Introduction, hierarchical clustering, partitional clustering (Ref.1, Chap.5) Artificial Neural Networks: Introduction, nets without hidden layers. nets with hidden layers, the back Propagation algorithms, Hopfield nets, an application.(Ref.1, Chap.6)

Processing of Waveforms and Images: Introduction, gray level sealing transfoniiations, equalization, geometric image and interpolation, Smoothing, transformations, edge detection, Laplacian and sharpening operators, line detection and template matching, logarithmic gray level sealing, the statistical significance of image features.(Ref.1, Chap.7) REFERENCE BOOKS:

1.Eart Gose, Richard Johnsonburg and Steve Joust, “Pattern

Recognition and Image Analysis”, Prentice-Hall of India-2003.

21

2.Duda and Hart, “Pattern recognition (Pattern recognition a scene

analysis)”

3.Robert J Schalkoff, “Pattern recognition : Statistical ,Structural and

neural approaches”, John Wiley

ADVANCED DIGITAL COMMUNICATIONS

Subject Code : 12EC006 IA Marks : 50

No. of Lecture Hours/Week : 04 Exam Hours : 03

Total No. of Lecture Hours : 52 Exam Marks : 100

Digital Modulation Techniques: Digital Modulation Formats, Coherent Binary Modulation Techniques, Coherent Quadrature –Modulation Techniques, NonCoherent Binary Modulation Techniques, Comparison of Binary and Quaternary Modulation Techniques, M-ary Modulation Techniques, Power Spectra, Bandwidth Efficiency, M-ary Modulation formats viewed in the Light of the channel capacity Theorem, Effect of Intersymbol Interference, Bit Versus Symbol Error Probabilities, Synchronisation, Applications.

Coding Techniques: Convolutional Encoding, Convolutional Encoder Representation, Formulation of the Convolutional Decoding Problem, Properties of Convolutional Codes: Distance property of convolutional codes, Systematic and Nonsystematic Convolutional Codes, Performance Bounds for Convolutional Codes, Coding Gain. Other Convolutional Decoding Algorithms: Sequential Decoding, Feedback Decoding,Turbo Codes.

Communication through band limited linear filter channels: Optimum receiver for channels with ISI and AWGN, Linear equalization, Decision-feedback equalization, reduced complexity ML detectors, Iterative equalization and decoding-Turbo equalization.

Adaptive Equalization: Adaptive linear equalizer, adaptive decision feedback equalizer, adaptive equalization of Trellis- coded signals, Recursive least squares algorithms for adaptive equalization, self recovering (blind) equalization.

22

Spread Spectrum Signals for Digital Communication: Model of Spread Spectrum Digital Communication System, Direct Sequence Spread Spectrum Signals, Frequency-Hopped Spread Spectrum Signals, CDMA, time-hopping SS, Synchronization of SS systems.

Digital Communication Through Fading Multi-Path Channels: Characterization of fading multi-path channels, the effect of signal characteristics on the choice of a channel model, frequency-Nonselective, slowly fading channel, diversity techniques for fading multi-path channels, Digital signal over a frequency-selective, slowly fading channel, coded wave forms for fading channels, multiple antenna systems.

REFERENCE BOOKS: 1. John G. Proakis, ―Digital Communications‖, 4th edition, McGraw Hill, 2001. 2. Bernard Sklar,

―”Digital Communications - Fundamentals and Applications”, 2nd

Edition Pearson Education (Asia) Pte. Ltd, 2001. 3. Simon Haykin, ― Digital Communications‖, John Wiley and Sons, 4. Andrew J. Viterbi, ―CDMA: Principles of Spread Spectrum Communications‖, Prentice Hall, USA, 1995. ---------------------------------------------------

ERROR CONTROL CODING


Introduction to Algebra: Groups, Fields, Binary Field Arithmetic, Construction of Galois Field GF (2m) and its basic properties, Computation using Galois Field GF (2m) Arithmetic, Vector spaces and Matrices.(Ref.1 Chap.2) Linear Block Codes: Generator and Parity check Matrices, Encoding circuits, Syndrome and Error Detection, Minimum Distance Considerations, Error detecting and Error correcting capabilities, Standard array and Syndrome decoding, Decoding circuits, Hamming Codes, Reed – Muller codes, The (24, 12) Golay code, Product codes and Interleaved codes.(Ref.1 Chap.3)

23

Cyclic Codes: Introduction, Generator and Parity check Polynomials, Encoding using Multiplication circuits, Systematic Cyclic codes – Encoding using Feed back shift register circuits, Generator matrix for Cyclic codes, Syndrome computation and Error detection, Meggitt decoder, Error trapping decoding, Cyclic Hamming codes, The (23, 12) Golay code, Shortened cyclic codes.(Ref.1 Chap.5)

BCH Codes: Binary primitive BCH codes, Decoding procedures, Implementation of Galois field Arithmetic, Implementation of Error correction. Non – binary BCH codes: q – ary Linear Block Codes, Primitive BCH codes over GF (q), Reed – Solomon Codes, Decoding of Non – Binary BCH and RS codes: The Berlekamp - Massey Algorithm.(Ref.1 Chap.6)

Majority Logic Decodable Codes: One – Step Majority logic decoding, one – step Majority logic decodable Codes, Two – step Majority logic decoding, Multiple – step Majority logic decoding.(Ref.1 Chap.8) Convolutional Codes: Encoding of Convolutional codes, Structural properties, Distance properties, Viterbi Decoding Algorithm for decoding, Soft – output Viterbi Algorithm, Stack and Fano sequential decoding Algorithms, Majority logic decoding(Ref.1 Chap.11)

Concatenated Codes & Turbo Codes: Single level Concatenated codes, Multilevel Concatenated codes, Soft decision Multistage decoding, Concatenated coding schemes with Convolutional Inner codes, Introduction to Turbo coding and their distance properties, Design of Turbo codes.(Ref.1 Chap.15)

Burst – Error – Correcting Codes: Burst and Random error correcting codes, Concept of Inter – leaving, cyclic codes for Burst Error correction – Fire codes, Convolutional codes for Burst Error correction.(Ref.1 Chap.21)

REFERENCE BOOKS:

1.Shu Lin & Daniel J. Costello, Jr. “Error Control Coding ” Pearson /

Prentice Hall, Second Edition, 2004. (Major Reference)

2.Blahut, R.E. “Theory and Practice of Error Control Codes”

Addison Wesley, 1984

ELECTIVE - IV

ADVANCES IN MEDICAL IMAGING

Subject Code : 12EC008 IA Marks : 50 No. of Lecture Hours /week : 04 Exam Hours : 03

24

Total no. of Lecture Hours : 52 Exam Marks : 100

1. Harmonic imaging in ultrasound, Sonoelastic imaging in ultrasound. 2. Concepts of spiral C.T, Microwave applications,. 3D imaging - Principles & application. 3. D imaging and its derivations in clinical research and practice, 4. Quantification in 3D imaging - S Evaluation of 3D imaging, High speed imaging in MRI / High resolution imaging, Flow & flow related magnetic resonance imaging REFERENCE BOOKS:

1. C.T.HERMAN & UDUPA, “3D Imaging in Medicine” CRC Press, 2000 2. Isaac N. Bankman, “Handbook of Medical Imaging” Academic press, 2000.

3. CHO & MANBIR SINGH, “Foundations of Medical Imaging”, John Wiley, 1993

4. Z.P.Liang & Paul C. Lauterbur, “Principles of MRI a signal processing perspective- 2000”, IEEE press

MOBILE COMPUTING


Wireless and Mobile Network Architecture: Principle of Cellular Communication, Overview 1G, 2G, 2.5G and 3G and 4G technologies. GSM Architecture and Mobility management hand off management, Network signaling. Mobile Computing fundamental challenges, Mobile Devices –PDA and mobile OS, PalmOs, Win CE and Symbian. Mobile IP Protocol Architecture: Mobile IP and IP v 6 and its application in mobile computing, Cellular Digital Packet Data CDPD, VOIP, GPRS Services, Wireless Local Loop-WLL system. Wireless Application Protocol (WAP): The Wireless Application Protocol application environment, wireless application protocol client software, hardware and websites, wireless application protocol gateways, implementing enterprise wireless application protocol strategy,

25

Wireless Markup Language: An Introduction to Wireless Technologies, Markup Languages , An Introduction to XML, Fundamentals of WML., Writing and Formatting Text , Navigating Between Cards and Decks, Displaying Images, Tables, Using Variables, Acquiring User Input

Wireless Markup Language Script: An Introduction to WMLScript, WMLScript Control Structures, Events, Phone.com Extensions, Usability Application of Mobile computing: ASP and Dynamic WAP Sites, XML and XSLT, Dynamic WML Generation with ASP and XSLT, Developing WAP Applications using Emulators. Distributed Mobile Computing: Distributed OS and file systems, Mobile Computing Software (Pervasive Computing) Development Strategies and tools, Data Management for Mobile Computing. REFERENCE BOOKS:

1.Yi Bing Lin, “Wireless and Mobile Networks Architecture”, John Wiley 2.Wrox, “The Beginning WML and WML Script ”, Wrox Publication 3.Tomasz Imielinski et.al, “Mobile Computing”, Kluwer Academic Press 1996 4.Uwe Hansmann, “Pervasive Computing Handbook. The Mobile World ”, IEE publication 2002 5.Jochen Burkhardt, et.al. “Pervasive Computing, Technology and Architecture of Mobile Internet Applications ”, Addison Wesley, 2002.

SIMULATION MODELING AND ANALYSIS

Subject Code : 12EC128 IA Marks : 50

No. of Lecture Hours/Week : 04 Exam Hours : 03

Total No. of Lecture Hours : 70 Exam Marks : 100

Basic simulation modeling: nature of simulation, system models, discrete event simulation, single server simulation, alternative approaches, other types of simulation.(Ref .1 Chap.1) Building valid, credible and detailed simulation models. Techniques for increasing model validity and credibility, comparing real world observations.

26

(Ref .1 Chap.5) Selecting input probability distributions. Useful probability distributions, assessing sample independence, activity I, II and III. Models of arrival process.(Ref .1 Chap.6) Random numbers generators: linear congruential, other kinds, testing random number generators. Random variate generation: approaches, continuous random variates, discrete random variates, correlated random variates.(Ref .1 Chap.7 & 8) Output data analysis. Statistical analysis for terminating simulations, analysis for steady state parameters. Comparing alternative system configurations. Confidence intervals. Variance reduction techniques. Antithetic and Control variates.(Ref .1 Chap.9) References: 1. Averill Law, “Simulation modeling and analysis”, MGH, 4th

edition, 2007 2. Jerry Banks, “Discrete event system simulation”, Pearson, 2009.

3. Seila, Ceric, Tadikamalla, “Applied simulation modeling”, Cengage, 2009.

4. George S. Fishman, “Discrete event simulation”, Springer, 2001. 5. Frank L. Severance, “System modeling and simulation”, Wiley, 2009

Documents

I SEMESTER LINEAR ALGEBRA Subject Codevtu.ac.in/pdf/pg2012/lspsyll.pdf · I SEMESTER LINEAR ALGEBRA Subject Code : ... Array fundamentals, ... Multichip module packaging and Wafer