000			03465nam a22004575i 4500
001			978-0-387-26871-2
003			DE-He213
005			20250710083936.0
007			cr nn 008mamaa
008			100301s2005 xxu| s |||| 0|eng d
020			_a9780387268712 _a99780387268712
024	7		_a10.1007/b138226 _2doi
082	0	4	_a519.2 _223
100	1		_aYin, G. George. _eauthor.
245	1	0	_aDiscrete-Time Markov Chains _h[recurso electrónico] : _bTwo-Time-Scale Methods and Applications / _cby G. George Yin, Qing Zhang.
264		1	_aNew York, NY : _bSpringer New York, _c2005.
300			_aXIX, 347 p. 13 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStochastic Modelling and Applied Probability, Applications of Mathematics, _x0172-4568 ; _v55
505	0		_aPrologue and Preliminaries -- Introduction, Overview, and Examples -- Mathematical Preliminaries -- Asymptotic Properties -- Asymptotic Expansions -- Occupation Measures -- Exponential Bounds -- Interim Summary and Extensions -- Applications -- Stability of Dynamic Systems -- Filtering -- Markov Decision Processes -- LQ Controls -- Mean-Variance Controls -- Production Planning -- Stochastic Approximation.
520			_aFocusing on discrete-time-scale Markov chains, the contents of this book are an outgrowth of some of the authors' recent research. The motivation stems from existing and emerging applications in optimization and control of complex hybrid Markovian systems in manufacturing, wireless communication, and financial engineering. Much effort in this book is devoted to designing system models arising from these applications, analyzing them via analytic and probabilistic techniques, and developing feasible computational algorithms so as to reduce the inherent complexity. This book presents results including asymptotic expansions of probability vectors, structural properties of occupation measures, exponential bounds, aggregation and decomposition and associated limit processes, and interface of discrete-time and continuous-time systems. One of the salient features is that it contains a diverse range of applications on filtering, estimation, control, optimization, and Markov decision processes, and financial engineering. This book will be an important reference for researchers in the areas of applied probability, control theory, operations research, as well as for practitioners who use optimization techniques. Part of the book can also be used in a graduate course of applied probability, stochastic processes, and applications.
650		0	_aMATHEMATICS.
650		0	_aDISTRIBUTION (PROBABILITY THEORY).
650	1	4	_aMATHEMATICS.
650	2	4	_aPROBABILITY THEORY AND STOCHASTIC PROCESSES.
650	2	4	_aCONTROL ENGINEERING.
650	2	4	_aOPERATIONS RESEARCH/DECISION THEORY.
650	2	4	_aAPPLICATIONS OF MATHEMATICS.
700	1		_aZhang, Qing. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387219486
830		0	_aStochastic Modelling and Applied Probability, Applications of Mathematics, _x0172-4568 ; _v55
856	4	0	_uhttp://dx.doi.org/10.1007/b138226 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c56596 _d56596