03789nam a22005895i 4500001001800000003000900018005001700027007001500044008004100059020003700100024002500137050001900162050001600181072001600197072001700213072002300230082001400253100002900267245013100296264004600427300003300473336002600506337002600532338003600558347002400594490009600618505041300714520134301127650001702470650002502487650002102512650002502533650002902558650001902587650002502606650001402631650001802645650001702663650004902680650003702729650004002766650003302806700002602839710003402865773002002899776003602919830009602955856003803051912001403089999001903103952007703122978-0-387-26871-2DE-He21320180115171351.0cr nn 008mamaa100301s2005 xxu| s |||| 0|eng d a97803872687129978-0-387-26871-27 a10.1007/b1382262doi 4aQA273.A1-274.9 4aQA274-274.9 7aPBT2bicssc 7aPBWL2bicssc 7aMAT0290002bisacsh04a519.22231 aYin, G. George.eauthor.10aDiscrete-Time Markov Chainsh[electronic resource] :bTwo-Time-Scale Methods and Applications /cby G. George Yin, Qing Zhang. 1aNew York, NY :bSpringer New York,c2005. aXX, 347 p.bonline resource. atextbtxt2rdacontent acomputerbc2rdamedia aonline resourcebcr2rdacarrier atext filebPDF2rda1 aStochastic Modelling and Applied Probability, Applications of Mathematics,x0172-4568 ;v550 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. 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. 0aMathematics. 0aOperations research. 0aDecision making. 0aApplied mathematics. 0aEngineering mathematics. 0aProbabilities. 0aControl engineering. 0aRobotics. 0aMechatronics.14aMathematics.24aProbability Theory and Stochastic Processes.24aControl, Robotics, Mechatronics.24aOperation Research/Decision Theory.24aApplications of Mathematics.1 aZhang, Qing.eauthor.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z9780387219486 0aStochastic Modelling and Applied Probability, Applications of Mathematics,x0172-4568 ;v5540uhttp://dx.doi.org/10.1007/b138226 aZDB-2-SMA c369305d369305 001040708EBookaelibbelibd2018-01-15r2018-01-15w2018-01-15yEBOOK