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007			cr nn 008mamaa
008			110125s2011 xxu| s |||| 0|eng d
020			_a9781441979704 _9978-1-4419-7970-4
040			_cMX-MeUAM
050		4	_aTK5102.9
050		4	_aTA1637-1638
050		4	_aTK7882.S65
082	0	4	_a621.382 _223
100	1		_aGray, Robert M. _eauthor.
245	1	0	_aEntropy and Information Theory _h[recurso electrónico] / _cby Robert M. Gray.
264		1	_aBoston, MA : _bSpringer US, _c2011.
300			_aXXVII, 409 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aPreface -- Introduction -- Information Sources -- Pair Processes: Channels, Codes, and Couplings -- Entropy -- The Entropy Ergodic Theorem -- Distortion and Approximation -- Distortion and Entropy -- Relative Entropy -- Information Rates -- Distortion vs. Rate -- Relative Entropy Rates -- Ergodic Theorems for Densities -- Source Coding Theorems -- Coding for Noisy Channels -- Bibliography -- References -- Index.
520			_aThis 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 codes Expanded discussion of results from ergodic theory relevant to information theory Expanded treatment of B-processes -- processes formed by stationary coding memoryless sources New material on trading off information and distortion, including the Marton inequality New material on the properties of optimal and asymptotically optimal source codes New material on the relationships of source coding and rate-constrained simulation or modeling of random processes Significant 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.
650		0	_aEngineering.
650		0	_aCoding theory.
650		0	_aDistribution (Probability theory).
650		0	_aTelecommunication.
650	1	4	_aEngineering.
650	2	4	_aSignal, Image and Speech Processing.
650	2	4	_aCommunications Engineering, Networks.
650	2	4	_aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
650	2	4	_aProbability Theory and Stochastic Processes.
650	2	4	_aCoding and Information Theory.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781441979698
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-1-4419-7970-4
596			_a19
942			_cLIBRO_ELEC
999			_c199955 _d199955