Information Theory And Coding Book

The work introduces the fundamentals concerning the measure of discrete information, the modeling of discrete sources without and with a memory, as well as of channels and coding. The understanding of the theoretical matter is supported by many examples. One particular emphasis is put on the explanation of Genomic Coding. Many examples throughout the book are chosen from this particular area

Information rate, entropy and mark off models are presented. Second and third chapter deals with source coding. Shannon's encoding algorithm, discrete communication channels, mutual information, Shannon's first theorem are also presented. Huffman coding and Shannon-Fano coding is also discussed. Continuous channels are discussed in fourth chapter.

The second difference between this book and the majority of other books on information theory or coding theory is that it covers both possible direc-tions probabilistic and algebraic. Typically, these lines of inquiry are presented in different monographs, textbooks and courses, often by people who work in different departments.

This book is an introduction to information and coding theory at the graduate or advanced undergraduate level. It assumes a basic knowledge of probability and modern algebra, but is otherwise self- contained. The intent is to describe as clearly as possible the fundamental issues involved in these subjects, rather than covering all aspects in an encyclopedic fashion.

quotInformation Theory and Codingquot Book Review This book provides a detailed coverage of Information Theory and Sources, including chapters on channels, mutual information, reliable messages through unreliable channels, and properties of codes. The book includes a glossary of symbols and expressions for a thorough understanding of the subject.

This revised edition of McEliece's classic is a self-contained introduction to all basic results in the theory of information and coding. This theory was developed to deal with the fundamental problem of communication, that of reproducing at one point, either exactly or approximately, a message selected at another point.

the corresponding information theory, from entropy and mutual information to channel capacity and the information transmission theorem. Finally, they provide insights into the connections between coding theory and other elds. Many worked examples are given throughout the book, using practical applications to illustrate theoretical deni-tions.

'This book offers a very good overview of information theory and coding issues enriched with interesting examples selected and proposed by two experienced researchers.' Jozef Woniak Source Zentralblatt MATH

Information Theory From Coding to Learning Polyanskiy, Yury, Wu, Yihong on Amazon.com. FREE shipping on qualifying offers. Information Theory From Coding to Learning 'Polyanskiy and Wu's book treats information theory and various subjects of statistics in a unique ensemble, a striking novelty in the literature.

Buy Information Theory and Coding by Example on Amazon.com FREE SHIPPING on qualified orders. Shortcuts menu Skip to. Main content Best Sellers Rank 7,352,421 in Books See Top 100 in Books 1,253 in Information Theory 1,281 in Discrete Mathematics Books 27,490 in Mathematics Books Customer Reviews 5.0 5.0 out of 5 stars 2 ratings.