Stochastic Stability of Differential Equations in Abstract Spaces

Author:   Kai Liu (Tianjin Normal University, China)
Publisher:   Cambridge University Press
ISBN:  

9781108705172


Pages:   276
Publication Date:   02 May 2019
Format:   Paperback
Availability:   In stock   Availability explained
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Stochastic Stability of Differential Equations in Abstract Spaces


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Overview

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.

Full Product Details

Author:   Kai Liu (Tianjin Normal University, China)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Dimensions:   Width: 15.20cm , Height: 1.60cm , Length: 22.80cm
Weight:   0.420kg
ISBN:  

9781108705172


ISBN 10:   1108705170
Pages:   276
Publication Date:   02 May 2019
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Reviews

'The text itself is rather detailed, and therefore can be understood by graduate students and young researchers who have taken a solid course in stochastic analysis. Many examples are provided throughout the text to explain the finer points in the results.' Maria J. Garrido-Atienza, MathSciNet


'The text itself is rather detailed, and therefore can be understood by graduate students and young researchers who have taken a solid course in stochastic analysis. Many examples are provided throughout the text to explain the finer points in the results.' Mar´ıa J. Garrido-Atienza, MathSciNet


Author Information

Kai Liu is a mathematician at the University of Liverpool. His research interests include stochastic analysis, both deterministic and stochastic partial differential equations, and stochastic control. His recent research activities focus on stochastic functional differential equations in abstract spaces. He is a member of the editorial boards of several international journals including the Journal of Stochastic Analysis and Applications and Statistics and Probability Letters.

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