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Item Details
Title: ENTROPY AND INFORMATION THEORY
By: Robert M. Gray
Format: Paperback

List price: £139.99


We currently do not stock this item, please contact the publisher directly for further information.

ISBN 10: 1489981322
ISBN 13: 9781489981325
Publisher: SPRINGER-VERLAG NEW YORK INC.
Pub. date: 18 September, 2014
Edition: 2nd ed. 2011
Pages: 409
Description: This fully updated new edition of the classic work on information theory presents a detailed analysis of Shannon-source and channel-coding theorems, before moving on to address sources, channels, codes and the properties of information and distortion measures.
Synopsis: This book is an updated version of the information theory classic, first published in 1990. About one-third of the book is devoted to Shannon source and channel coding theorems; the remainder addresses sources, channels, and codes and on information and distortion measures and their properties. New in this edition:Expanded treatment of stationary or sliding-block codes and their relations to traditional block codesExpanded discussion of results from ergodic theory relevant to information theoryExpanded treatment of B-processes -- processes formed by stationary coding memoryless sourcesNew material on trading off information and distortion, including the Marton inequalityNew material on the properties of optimal and asymptotically optimal source codesNew material on the relationships of source coding and rate-constrained simulation or modeling of random processesSignificant material not covered in other information theory texts includes stationary/sliding-block codes, a geometric view of information theory provided by process distance measures, and general Shannon coding theorems for asymptotic mean stationary sources, which may be neither ergodic nor stationary, and d-bar continuous channels.
Illustrations: XXVII, 409 p.
Publication: US
Imprint: Springer-Verlag New York Inc.
Returns: Returnable
Some other items by this author:
AN INTRODUCTION TO STATISTICAL SIGNAL PROCESSING
AN INTRODUCTION TO STATISTICAL SIGNAL PROCESSING (HB)
AN INTRODUCTION TO STATISTICAL SIGNAL PROCESSING (PB)
ENTROPY AND INFORMATION THEORY (HB)
FOURIER TRANSFORMS (HB)
FOURIER TRANSFORMS (PB)
IMAGE SEGMENTATION AND COMPRESSION USING HIDDEN MARKOV MODELS (HB)
IMAGE SEGMENTATION AND COMPRESSION USING HIDDEN MARKOV MODELS (PB)
LINEAR PREDICTIVE CODING AND THE INTERNET PROTOCOL (HB)
PROBABILITY, RANDOM PROCESSES, AND ERGODIC PROPERTIES (HB)
PROBABILITY, RANDOM PROCESSES, AND ERGODIC PROPERTIES (PB)
SOURCE CODING THEORY (HB)
SOURCE CODING THEORY (PB)
STOCHASTIC IMAGE PROCESSING (HB)
STOCHASTIC IMAGE PROCESSING (PB)
TECHNOLOGY INTEGRATION IN HIGHER EDUCATION (HB)
TOEPLITZ AND CIRCULANT MATRICES (PB)
VECTOR QUANTIZATION AND SIGNAL COMPRESSION (HB)
VECTOR QUANTIZATION AND SIGNAL COMPRESSION (PB)

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