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Stochastic stability of differential equations in abstract spaces / Kai Liu.

By: Material type: TextTextSeries: London Mathematical Society lecture note series ; 453.Publisher: Cambridge : Cambridge University Press, 2019Description: 1 online resource (ix, 266 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781108653039 (ebook)
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 515/.35 23
LOC classification:
  • QA274.23 .L5825 2019
Online resources:
Contents:
Preliminaries -- Stability of linear stochastic differential equations -- Stability of non linear stochastic differential equations -- Stability of stochastic functional differential equations -- Some applications related to stochastic stability.
Summary: 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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Title from publisher's bibliographic system (viewed on 26 Mar 2019).

Preliminaries -- Stability of linear stochastic differential equations -- Stability of non linear stochastic differential equations -- Stability of stochastic functional differential equations -- Some applications related to stochastic stability.

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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