 INFORMATION THEORY & CODING Ebook and Lecture Notes PDF

Ravi Chopra | 16-Jan-2016 |

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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