Vector Quantization and Signal Compression

Name: Vector Quantization and Signal Compression
Brand: Springer
SKU: 9780792391814
Price: 42335 HUF
Availability: InStock

Szerző: Allen Gersho, Robert M. Gray

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer

Elérhetőség: Beszállítói készleten

Küldés 10-13 napon belül

42 335 Ft

Herb Caen, a popular columnist for the San Francisco Chronicle, recently quoted a Voice of America p...

Információk a könyvről

Szerző

Allen Gersho, Robert M. Gray

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

1991

oldal

732

EAN

9780792391814

ISBN

0792391810

Enbook ID

01398089

Kiadó

Springer

Súly

2720

Méretek

155 x 235 x 46

Teljes leírás

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.

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Vector Quantization and Signal Compression

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