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INFORMATION THEORY & CODING Ebook and Lecture Notes PDF
Ravi Chopra

INFORMATION THEORY & CODING Ebook and Lecture Notes PDF

Ravi Chopra | 16-Jan-2016 |
Information Theory and Source Coding , Waveform coding , Introduction to Error correcting codes , Linear Block codes , Cyclic Codes , Well-Known Block Codes , Convolutional Encoding , Convolutional Encoder Representation , Formulation of the Convolutional Decoding Problem , Other Convolutional Decoding Algorithms , Reed-Solomon Codes , Turbo Codes ,

Hi friends, here Ravi Chopra uploaded notes for INFORMATION THEORY & CODING with title INFORMATION THEORY & CODING Ebook and Lecture Notes PDF. You can download this lecture notes, ebook by clicking on the below file name or icon.

Module –I (8Hours)
Information Theory and Source Coding
Introduction to Information Theory, Uncertainty and Information, Average Mutual Information and
Entropy, Information
Measures for Continuous Random Variables, waveform sources
Amplitude Quantizing: quantizing noise, uniform quantizing, non-uniform quantizing
Differential Pulse Code Modulation: one-tap prediction, N-tap prediction, delta modulation, sigma delta
modulation,
sigma delta A-to-D convertor(ADC), sigma delta D-to-A convertor(DAC)
Block coding: vector quantizing, Transform Coding: quantization for transform coding, Sub-band Coding
Source Coding for Digital Data: properties of codes, Huffman codes, Run-length codes
Module –II (12Hours)
Waveform coding: Antipodal and Orthogonal signals, Orthogonal and Biorthogonal codes, waveform
coding system
example, Types of error control: Terminal connectivity, automatic repeat request
Structured Sequence: Channel models, Channel capacity, Channel coding, Information Capacity Theorem,
The Shannon
Limit, Introduction to Error correcting codes, code rate & redundancy, parity check codes: Single parity
check code,
Rectangular code
Linear Block codes: vector spaces, vector subspaces, A(6,3) linear block code example, Generator matrix,
systematic
linear block codes, parity-check matrix, syndrome testing, error correction , Decoder implementation
Error Detecting & Correcting Capability: weight & distance of binary vectors, minimum distance of linear
code, error
detection & correction, visualization of a 6-tuple space, erasure correction
Usefulness of Standard Array: estimating code capability, an (n, k) example, designing the (8,2) code,
error detection vs.
error correction trade-off
Cyclic Codes: algebraic structures of cyclic code, binary cyclic code properties, encoding in systematic
form, circuit for
dividing polynomial, systematic encoding with an (n-k)-stage shift register, error detection with an (n-k)-
shift register
Well-Known Block Codes: Hamming codes, extended Golay code, BCH codes.
Module –III (12Hours)
Convolutional Encoding, Convolutional Encoder Representation: connection representation, state
representation & the
state diagram, the tree diagram, the trellis diagram
Formulation of the Convolutional Decoding Problem: maximum likelihood decoding, channel models:
hard versus soft
decisions, Viterbi Convolutional Decoding Algorithm, an example of viterbi convolutional decoding,
decoder
implementation, path memory and synchronization
Properties of Convolutional Codes: distance properties of convolutional codes, systematic & nonsystematic
convolutional codes, catastrophic error propagation in convolutional codes, performance bounds for
convolutional codes,
coding gain, based known convolutional codes, convolutional code rate trade-off, soft-decision viterbi
decoding
Other Convolutional Decoding Algorithms: sequential decoding, comparisons & limitations of viterbi &
sequential
decoding, feedback decoding.
Module –IV (8Hours)
Reed-Solomon Codes: Reed-Solomon Error Probability, Why R-S codes perform well against burst noise,
R-S
performance as a function of size, redundancy, and code rate
Interleaving & Concatenated Codes: Block interleaving, Convolutional interleaving, concatenated codes
Coding & Interleaving Applied to CD Digital Audio System: CIRC encodings, CIRC decoding,
interpolation & muting
Turbo Codes: turbo code concepts, log-likelihood algebra

 

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