Skip to main content Accessibility help
×
  1. Home
  2. Browse subjects
  3. Statistics and Probability
  4. Probability theory and stochastic processes
  5. Content listing

Refine search

Refine search

Access:
Content type:
Publication date:
Apply   From and To filters
Subject: Show more
Journals Show more
Publishers: Show more
Societies Show more
Series: Show more
Collections: Show more

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

3044 results in Probability theory and stochastic processes

Page 32 of 153

  • 1 - Preliminaries

  • Kai Liu, Tianjin Normal University, China
  • Book:
    Stochastic Stability of Differential Equations in Abstract Spaces
    Published online:
    19 April 2019
    Print publication:
    02 May 2019, pp 1-45
    • Chapter
      • You have access
    • PDF
    • Export citation

  • Summary

    In this chapter, we shall recall some definitions and results from functional analysis, partial differential equations, and probability theories. We introduce two notions of solutions, strong and mild, for stochastic differential equations in Hilbert spaces. We also introduce and clarify various definitions of stochastic stability in abstract spaces, which are a natural generalization of deterministic stability concepts.

Stochastic Stability of Differential Equations in Abstract Spaces
  • Kai Liu
  • Published online:
    19 April 2019
    Print publication:
    02 May 2019
  • 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.

Page 32 of 153