Probability Theory and Stochastic Modelling: Linear Theory and Applications to Non-Linear Filtering
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Probability Theory and Stochastic Modelling: Linear Theory and Applications to Non-Linear Filtering
Rozovsky, Boris L.; Lototsky, Sergey V.
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.
Details
Published by: Springer
Publication Date: 2018-10-15
Format: Hardcover
ISBN-13: 9783319948928
DOI: 10.1007/978-3-319-94893-5
Dimensions: 235cm x155cm
Pages: 330