Stochastic evolution systems : linear theory and applications to non-linear filtering
- 作者： Rozovsky, Boris L., author.
- 其他作者：
- 其他題名：
- Probability theory and stochastic modelling ;
- 出版： Cham : Springer International Publishing :Imprint: Springer
- 版本：Second edition.
- 叢書名： Probability theory and stochastic modelling,volume 89
- 主題： Stochastic partial differential equations. , Probability Theory and Stochastic Processes. , Partial Differential Equations. , Functional Analysis. , Electrical Engineering. , Theoretical, Mathematical and Computational Physics.
- ISBN： 9783319948935 (electronic bk.) 、 9783319948928 (paper)
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FIND@SFXID:
CGU
- 資料類型: 電子書
- 內容註: 1 Examples and Auxiliary Results -- 2 Stochastic Integration in a Hilbert Space -- 3 Linear Stochastic Evolution Systems in Hilbert Spaces -- 4 Ito's Second Order Parabolic Equations -- 5 Ito's Partial Differential Equations and Diffusion Processes -- 6 Filtering, Interpolation and Extrapolation of Diffusion Processes -- 7 Hypoellipticity of Ito's Second Order Parabolic Equations -- 8 Chaos Expansion for Linear Stochastic Evolution Systems -- Notes -- References -- Index.
- 摘要註: This monograph, now in a thoroughly revised second edition, develops the theory of stochastic calculus in Hilbert spaces and applies the results to the study of generalized solutions of stochastic parabolic equations. The emphasis lies on second-order stochastic parabolic equations and their connection to random dynamical systems. The authors further explore applications to the theory of optimal non-linear filtering, prediction, and smoothing of partially observed diffusion processes. The new edition now also includes a chapter on chaos expansion for linear stochastic evolution systems. This book will appeal to anyone working in disciplines that require tools from stochastic analysis and PDEs, including pure mathematics, financial mathematics, engineering and physics.
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讀者標籤：
- 系統號： 005437756 | 機讀編目格式
館藏資訊
This monograph, now in a thoroughly revised second edition, develops the theory of stochastic calculus in Hilbert spaces and applies the results to the study of generalized solutions of stochastic parabolic equations. The emphasis lies on second-order stochastic parabolic equations and their connection to random dynamical systems. The authors further explore applications to the theory of optimal non-linear filtering, prediction, and smoothing of partially observed diffusion processes. The new edition now also includes a chapter on chaos expansion for linear stochastic evolution systems. This book will appeal to anyone working in disciplines that require tools from stochastic analysis and PDEs, including pure mathematics, financial mathematics, engineering and physics.