Hybrid Switching Diffusions

Hybrid Switching Diffusions

EnglishHardbackPrint on demand
Yin G. George
Springer-Verlag New York Inc.
EAN: 9781441911049
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Detailed information

This book encompasses the study of hybrid switching di usion processes and their applications. The word \hybrid" signi es the coexistence of c- tinuous dynamics and discrete events, which is one of the distinct features of the processes under consideration. Much of the book is concerned with the interactions of the continuous dynamics and the discrete events. Our motivations for studying such processes originate from emerging and - isting applications in wireless communications, signal processing, queueing networks, production planning, biological systems, ecosystems, nancial engineering, and modeling, analysis, and control and optimization of lar- scale systems, under the in uence of random environments. Displaying mixture distributions, switching di usions may be described by the associated operators or by systems of stochastic di erential eq- tions together with the probability transition laws of the switching actions. We either have Markov-modulated switching di usions or processes with continuous state-dependent switching. The latter turns out to be much more challenging to deal with. Viewing the hybrid di usions as a number of di usions joined together by the switching process, they may be se- ingly not much di erent from their di usion counterpart. Nevertheless, the underlying problems become more di cult to handle, especially when the switching processes depend on continuous states. The di culty is due to the interaction of the discrete and continuous processes and the tangled and hybrid information pattern.
EAN 9781441911049
ISBN 1441911049
Binding Hardback
Publisher Springer-Verlag New York Inc.
Publication date October 26, 2009
Pages 398
Language English
Dimensions 235 x 155
Country United States
Readership Professional & Scholarly
Authors Yin G. George; Zhu Chao
Illustrations XVIII, 398 p.
Edition 2010 ed.
Series Stochastic Modelling and Applied Probability
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