000 03760nam a22005895i 4500
001 978-0-387-26871-2
003 DE-He213
005 20180115171351.0
007 cr nn 008mamaa
008 100301s2005 xxu| s |||| 0|eng d
020 _a9780387268712
_9978-0-387-26871-2
024 7 _a10.1007/b138226
_2doi
050 4 _aQA273.A1-274.9
050 4 _aQA274-274.9
072 7 _aPBT
_2bicssc
072 7 _aPBWL
_2bicssc
072 7 _aMAT029000
_2bisacsh
082 0 4 _a519.2
_223
100 1 _aYin, G. George.
_eauthor.
245 1 0 _aDiscrete-Time Markov Chains
_h[electronic resource] :
_bTwo-Time-Scale Methods and Applications /
_cby G. George Yin, Qing Zhang.
264 1 _aNew York, NY :
_bSpringer New York,
_c2005.
300 _aXX, 347 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_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 _aOperations research.
650 0 _aDecision making.
650 0 _aApplied mathematics.
650 0 _aEngineering mathematics.
650 0 _aProbabilities.
650 0 _aControl engineering.
650 0 _aRobotics.
650 0 _aMechatronics.
650 1 4 _aMathematics.
650 2 4 _aProbability Theory and Stochastic Processes.
650 2 4 _aControl, Robotics, Mechatronics.
650 2 4 _aOperation 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
912 _aZDB-2-SMA
999 _c369305
_d369305