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035   $a(UkCbUP)CR9781139208468
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101 0 $aeng
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181   $ctxt$2rdacontent
182   $cc$2rdamedia
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200 10$aNon-homogeneous random walks $eLyapunov function methods for near-critical stochastic systems /$fMikhail Menshikov, University of Durham, Serguei Popov, Universidade Estadual de Campinas, Brazil, Andrew Wade, University of Durham$b[electronic resource]
210  1$aCambridge :$cCambridge University Press,$d2017.
215   $a1 online resource (xviii, 363 pages) $cdigital, PDF file(s)
225 1 $aCambridge tracts in mathematics ;$v209
300   $aTitle from publisher's bibliographic system (viewed on 28 Feb 2017).
311   $a1-107-02669-5 
311   $a1-316-86880-X 
330   $aStochastic systems provide powerful abstract models for a variety of important real-life applications: for example, power supply, traffic flow, data transmission. They (and the real systems they model) are often subject to phase transitions, behaving in one way when a parameter is below a certain critical value, then switching behaviour as soon as that critical value is reached. In a real system, we do not necessarily have control over all the parameter values, so it is important to know how to find critical points and to understand system behaviour near these points. This book is a modern presentation of the 'semimartingale' or 'Lyapunov function' method applied to near-critical stochastic systems, exemplified by non-homogeneous random walks. Applications treat near-critical stochastic systems and range across modern probability theory from stochastic billiards models to interacting particle systems. Spatially non-homogeneous random walks are explored in depth, as they provide prototypical near-critical systems.
410  0$aCambridge tracts in mathematics ;$v209.
606   $aRandom walks (Mathematics)
606   $aStochastic processes
615  0$aRandom walks (Mathematics)
615  0$aStochastic processes.
676   $a519.2/82
700   $aMen?shikov$b M. V$g(Mikhail Vasil?evich),$0850776
702   $aPopov$b Serguei$f1972-
702   $aWade$b Andrew$g(Andrew R.),$f1981-
801  0$bUkCbUP
801  1$bUkCbUP
906   $aBOOK
912   $a9910159458503321
996   $aNon-homogeneous random walks$91899644
997   $aUNINA