Introduction To Information Theory


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Introduction to Information Theory and Data Compression


Introduction to Information Theory and Data Compression

Author: Peter D. Johnson Jr.

language: en

Publisher: CRC Press

Release Date: 2003-02-26


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An effective blend of carefully explained theory and practical applications, this text imparts the fundamentals of both information theory and data compression. Although the two topics are related, this unique text allows either topic to be presented independently, and it was specifically designed so that the data compression section requires no pr

An Introduction to Single-User Information Theory


An Introduction to Single-User Information Theory

Author: Fady Alajaji

language: en

Publisher: Springer

Release Date: 2018-04-24


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This book presents a succinct and mathematically rigorous treatment of the main pillars of Shannon’s information theory, discussing the fundamental concepts and indispensable results of Shannon’s mathematical theory of communications. It includes five meticulously written core chapters (with accompanying problems), emphasizing the key topics of information measures; lossless and lossy data compression; channel coding; and joint source-channel coding for single-user (point-to-point) communications systems. It also features two appendices covering necessary background material in real analysis and in probability theory and stochastic processes. The book is ideal for a one-semester foundational course on information theory for senior undergraduate and entry-level graduate students in mathematics, statistics, engineering, and computing and information sciences. A comprehensive instructor’s solutions manual is available.

Introduction to Coding and Information Theory


Introduction to Coding and Information Theory

Author: Steven Roman

language: en

Publisher: Springer Science & Business Media

Release Date: 1996-11-26


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This book is intended to introduce coding theory and information theory to undergraduate students of mathematics and computer science. It begins with a review of probablity theory as applied to finite sample spaces and a general introduction to the nature and types of codes. The two subsequent chapters discuss information theory: efficiency of codes, the entropy of information sources, and Shannon's Noiseless Coding Theorem. The remaining three chapters deal with coding theory: communication channels, decoding in the presence of errors, the general theory of linear codes, and such specific codes as Hamming codes, the simplex codes, and many others.