Stochastic Stability of Differential Equations in Abstract Spaces
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.
- Provides a basic, friendly and accessible introduction, ideal for graduates and young researchers
- Presents the topic systematically, with minimal prerequisites
- Brings the subject together cohesively, drawing on widespread literature
Reviews & endorsements
'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
Product details
May 2019Paperback
9781108705172
276 pages
228 × 152 × 16 mm
0.42kg
Available
Table of Contents
- Preface
- 1. Preliminaries
- 2. Stability of linear stochastic differential equations
- 3. Stability of non linear stochastic differential equations
- 4. Stability of stochastic functional differential equations
- 5. Some applications related to stochastic stability
- Appendix
- References
- Index.
