Stochastic Stability of Differential Equations in Abstract Spaces

Nonfiction, Science & Nature, Mathematics, Differential Equations, Statistics
Cover of the book Stochastic Stability of Differential Equations in Abstract Spaces by Kai Liu, Cambridge University Press
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Author: Kai Liu ISBN: 9781108626491
Publisher: Cambridge University Press Publication: May 2, 2019
Imprint: Cambridge University Press Language: English
Author: Kai Liu
ISBN: 9781108626491
Publisher: Cambridge University Press
Publication: May 2, 2019
Imprint: Cambridge University Press
Language: English

The stability of stochastic differential equations in abstract, mainly Hilbert, spaces receives a unified treatment in this self-contained book. It covers basic theory as well as computational techniques for handling the stochastic stability of systems from mathematical, physical and biological problems. Its core material is divided into three parts devoted respectively to the stochastic stability of linear systems, non-linear systems, and time-delay systems. The focus is on stability of stochastic dynamical processes affected by white noise, which are described by partial differential equations such as the Navier–Stokes equations. A range of mathematicians and scientists, including those involved in numerical computation, will find this book useful. It is also ideal for engineers working on stochastic systems and their control, and researchers in mathematical physics or biology.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The stability of stochastic differential equations in abstract, mainly Hilbert, spaces receives a unified treatment in this self-contained book. It covers basic theory as well as computational techniques for handling the stochastic stability of systems from mathematical, physical and biological problems. Its core material is divided into three parts devoted respectively to the stochastic stability of linear systems, non-linear systems, and time-delay systems. The focus is on stability of stochastic dynamical processes affected by white noise, which are described by partial differential equations such as the Navier–Stokes equations. A range of mathematicians and scientists, including those involved in numerical computation, will find this book useful. It is also ideal for engineers working on stochastic systems and their control, and researchers in mathematical physics or biology.

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