Introduction to Information Theory and Data Compression

Jr. Johnson, Greg A. Harris, D.C. Hankerson

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English

Chapman & Hall/CRC
25 September 2019

Discrete mathematics; Combinatorics & graph theory; Computing: general; Computer science

Series: Applied Mathematics

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 prior knowledge of information theory.

The treatment of information theory, while theoretical and abstract, is quite elementary, making this text less daunting than many others. After presenting the fundamental definitions and results of the theory, the authors then apply the theory to memoryless, discrete channels with zeroth-order, one-state sources.

The chapters on data compression acquaint students with a myriad of lossless compression methods and then introduce two lossy compression methods. Students emerge from this study competent in a wide range of techniques. The authors' presentation is highly practical but includes some important proofs, either in the text or in the exercises, so instructors can, if they choose, place more emphasis on the mathematics.

Introduction to Information Theory and Data Compression, Second Edition is ideally suited for an upper-level or graduate course for students in mathematics, engineering, and computer science.

Features:

Expanded discussion of the historical and theoretical basis of information theory that builds a firm, intuitive grasp of the subject

Reorganization of theoretical results along with new exercises, ranging from the routine to the more difficult, that reinforce students' ability to apply the definitions and results in specific situations.

Simplified treatment of the algorithm(s) of Gallager and Knuth

Discussion of the information rate of a code and the trade-off between error correction and information rate

Treatment of probabilistic finite state source automata, including basic resul

By: Jr. Johnson, Greg A. Harris, D.C. Hankerson
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Edition: 2nd edition
Dimensions: Height: 234mm, Width: 156mm,
Weight: 700g
ISBN: 9780367395438
ISBN 10: 0367395436
Series: Applied Mathematics
Pages: 384
Publication Date: 25 September 2019
Audience: College/higher education , General/trade , Primary , ELT Advanced
Format: Paperback
Publisher's Status: Active

Johnson, Jr.; Harris, Greg A.; Hankerson, D.C.

Reviews for Introduction to Information Theory and Data Compression

Statisticians, applied mathematicians, engineers, and computer scientists will find this well-written book useful. -Journal of Statistical Computation and Simulation