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Information Theory and Coding by K Giridhar: A Review



Information Theory and Coding by K Giridhar: A Review




Information theory and coding are two important topics in the field of communication engineering. They deal with the efficient representation and transmission of information over noisy channels. Information theory provides the fundamental limits and principles of data compression and error correction, while coding provides the practical methods and algorithms to achieve them.




information theory and coding by k giridhar pdf free


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One of the books that covers these topics in a comprehensive and accessible way is Information Theory & Coding by K Giridhar, published by Pooja Publications in 2010. This book is intended for undergraduate students of electronics and communication engineering, as well as for anyone who wants to learn the basics of information theory and coding.


The book consists of eight chapters, each with a clear introduction, examples, exercises, and references. The first chapter introduces the various measures of information, such as entropy, mutual information, and channel capacity. The second and third chapters deal with source coding, which is the process of compressing data to reduce redundancy. The book covers both lossless and lossy compression techniques, such as Huffman coding, Shannon-Fano coding, run-length encoding, and transform coding.


The fourth chapter discusses continuous channels, which are channels that can transmit analog signals. The book explains how to model and analyze continuous channels using probability density functions, signal-to-noise ratios, bandwidths, and power spectral densities. The book also introduces the concept of channel coding theorem, which states that reliable communication is possible over any noisy channel if the transmission rate is below the channel capacity.


The fifth, sixth, and seventh chapters focus on channel coding, which is the process of adding redundancy to data to protect it from errors. The book covers both block codes and convolutional codes, which are two types of error-correcting codes. Block codes are codes that divide the data into fixed-length blocks and add parity bits to each block. Convolutional codes are codes that use a sliding window to encode the data using feedback shift registers. The book explains how to design, encode, decode, and evaluate different types of block codes and convolutional codes, such as linear codes, Hamming codes, cyclic codes, Reed-Solomon codes, Golay codes, turbo codes, and Viterbi decoding.


The eighth chapter presents some other aspects of coding theory, such as cryptography, secret sharing, network coding, quantum coding, and DNA coding. These topics are briefly introduced and some examples are given to illustrate their applications.


The book is well-written and easy to follow. It provides a good balance between theory and practice. It covers both classical and modern topics in information theory and coding. It also includes many diagrams, tables, graphs, and numerical examples to help the reader understand the concepts and calculations. The book is suitable for self-study as well as for classroom use. e0e6b7cb5c


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