Asymptotic Analysis for Functional Stochastic Differential Equations

Nonfiction, Science & Nature, Mathematics, Differential Equations, Statistics
Cover of the book Asymptotic Analysis for Functional Stochastic Differential Equations by Jianhai Bao, George Yin, Chenggui Yuan, Springer International Publishing
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Author: Jianhai Bao, George Yin, Chenggui Yuan ISBN: 9783319469799
Publisher: Springer International Publishing Publication: November 19, 2016
Imprint: Springer Language: English
Author: Jianhai Bao, George Yin, Chenggui Yuan
ISBN: 9783319469799
Publisher: Springer International Publishing
Publication: November 19, 2016
Imprint: Springer
Language: English

This brief treats dynamical systems that involve delays and random disturbances. The study is motivated by a wide variety of systems in real life in which random noise has to be taken into consideration and the effect of delays cannot be ignored. Concentrating on such systems that are described by functional stochastic differential equations, this work focuses on the study of large time behavior, in particular, ergodicity.

This brief is written for probabilists, applied mathematicians, engineers, and scientists who need to use delay systems and functional stochastic differential equations in their work. Selected topics from the brief can also be used in a graduate level topics course in probability and stochastic processes.

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This brief treats dynamical systems that involve delays and random disturbances. The study is motivated by a wide variety of systems in real life in which random noise has to be taken into consideration and the effect of delays cannot be ignored. Concentrating on such systems that are described by functional stochastic differential equations, this work focuses on the study of large time behavior, in particular, ergodicity.

This brief is written for probabilists, applied mathematicians, engineers, and scientists who need to use delay systems and functional stochastic differential equations in their work. Selected topics from the brief can also be used in a graduate level topics course in probability and stochastic processes.

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