---

＜電子ブック＞
Invariant Probabilities of Transition Functions / by Radu Zaharopol
(Probability and Its Applications)

版	1st ed. 2014.
出版者	Cham : Springer International Publishing : Imprint: Springer
出版年	2014
本文言語	英語
大きさ	XVIII, 389 p : online resource
著者標目	*Zaharopol, Radu author SpringerLink (Online service)
件　名	LCSH:Operator theory LCSH:Dynamical systems LCSH:Probabilities LCSH:Potential theory (Mathematics) LCSH:Measure theory FREE:Operator Theory FREE:Dynamical Systems FREE:Probability Theory FREE:Potential Theory FREE:Measure and Integration
一般注記	Introduction -- 1.Transition Probabilities -- 2.Transition Functions -- 3.Vector Integrals and A.E. Convergence -- 4.Special Topics -- 5.The KBBY Ergodic Decomposition, Part I -- 6.The KBBY Ergodic Decomposition, Part II -- 7.Feller Transition Functions -- Appendices: A.Semiflows and Flows: Introduction -- B.Measures and Convolutions -- Bibliography -- Index The structure of the set of all the invariant probabilities and the structure of various types of individual invariant probabilities of a transition function are two topics of significant interest in the theory of transition functions, and are studied in this book. The results obtained are useful in ergodic theory and the theory of dynamical systems, which, in turn, can be applied in various other areas (like number theory). They are illustrated using transition functions defined by flows, semiflows, and one-parameter convolution semigroups of probability measures. In this book, all results on transition probabilities that have been published by the author between 2004 and 2008 are extended to transition functions. The proofs of the results obtained are new. For transition functions that satisfy very general conditions the book describes an ergodic decomposition that provides relevant information on the structure of the corresponding set of invariant probabilities. Ergodic decomposition means a splitting of the state space, where the invariant ergodic probability measures play a significant role. Other topics covered include: characterizations of the supports of various types of invariant probability measures and the use of these to obtain criteria for unique ergodicity, and the proofs of two mean ergodic theorems for a certain type of transition functions. The book will be of interest to mathematicians working in ergodic theory, dynamical systems, or the theory of Markov processes. Biologists, physicists and economists interested in interacting particle systems and rigorous mathematics will also find this book a valuable resource. Parts of it are suitable for advanced graduate courses. Prerequisites are basic notions and results on functional analysis, general topology, measure theory, the Bochner integral and some of its applications HTTP:URL=https://doi.org/10.1007/978-3-319-05723-1

 類似資料