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Item Details
Title: VECTOR QUANTIZATION AND SIGNAL COMPRESSION
By: Allen Gersho, Robert M. Gray
Format: Hardback

List price: £89.99


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ISBN 10: 0792391810
ISBN 13: 9780792391814
Publisher: SPRINGER
Pub. date: 30 November, 1991
Edition: 1992 ed.
Series: The Springer International Series in Engineering and Computer Science 159
Pages: 732
Synopsis: Herb Caen, a popular columnist for the San Francisco Chronicle, recently quoted a Voice of America press release as saying that it was reorganizing in order to "eliminate duplication and redundancy. " This quote both states a goal of data compression and illustrates its common need: the removal of duplication (or redundancy) can provide a more efficient representation of data and the quoted phrase is itself a candidate for such surgery. Not only can the number of words in the quote be reduced without losing informa- tion, but the statement would actually be enhanced by such compression since it will no longer exemplify the wrong that the policy is supposed to correct. Here compression can streamline the phrase and minimize the em- barassment while improving the English style. Compression in general is intended to provide efficient representations of data while preserving the essential information contained in the data. This book is devoted to the theory and practice of signal compression, i. e. , data compression applied to signals such as speech, audio, images, and video signals (excluding other data types such as financial data or general- purpose computer data). The emphasis is on the conversion of analog waveforms into efficient digital representations and on the compression of digital information into the fewest possible bits. Both operations should yield the highest possible reconstruction fidelity subject to constraints on the bit rate and implementation complexity.
Illustrations: XXIII, 732 p.
Publication: Netherlands
Imprint: Springer
Returns: Returnable
Some other items by this author:
ADVANCES IN SPEECH CODING (HB)
ADVANCES IN SPEECH CODING (PB)
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)
ENTROPY AND INFORMATION THEORY (PB)
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)
SPEECH AND AUDIO CODING FOR WIRELESS AND NETWORK APPLICATIONS (HB)
SPEECH AND AUDIO CODING FOR WIRELESS AND NETWORK APPLICATIONS (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 (PB)

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