Random Fields and Stochastic Partial Differential Equations

Y. Rozanov

ISBN 10: 0792349849 / ISBN 13: 9780792349846

Published by Springer Netherlands, Springer Netherlands, 1998

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This book considers some models described by means of partial dif ferential equations and boundary conditions with chaotic stochastic disturbance. In a framework of stochastic Partial Differential Equa tions an approach is suggested to generalize solutions of stochastic Boundary Problems. The main topic concerns probabilistic aspects with applications to well-known Random Fields models which are representative for the corresponding stochastic Sobolev spaces. {The term 'stochastic' in general indicates involvement of appropriate random elements. ) It assumes certain knowledge in general Analysis and Probability {Hilbert space methods, Schwartz distributions, Fourier transform) . I A very general description of the main problems considered can be given as follows. Suppose, we are considering a random field ~ in a region T ~ Rd which is associated with a chaotic (stochastic) source'' by means of the differential equation (\*) in T. A typical chaotic source can be represented by an appropri ate random field'' with independent values, i. e. , generalized random function'' = ( cp, 'TJ), cp E C~(T), with independent random variables ( cp, 'fJ) for any test functions cp with disjoint supports. The property of having independent values implies a certain 'roughness' of the ran dom field '' which can only be treated functionally as a very irregular Schwarz distribution. With the lack of a proper development of non linear analyses for generalized functions, let us limit ourselves to the 1 For related material see, for example, J. L. Lions, E.

Seller Inventory # 9780792349846

Bibliographic Details

• Title: Random Fields and Stochastic Partial Differential Equations
• Publisher: Springer Netherlands, Springer Netherlands
• Publication Date: 1998
• Language: English
• ISBN 10: 0792349849
• ISBN 13: 9780792349846
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 18D millimeters 241 millimeters width by 160 millimeters height by 18 millimeters depth
• Weight: 535 grams

About this title

Synopsis

This book considers some models described by means of partial dif­ ferential equations and boundary conditions with chaotic stochastic disturbance. In a framework of stochastic Partial Differential Equa­ tions an approach is suggested to generalize solutions of stochastic Boundary Problems. The main topic concerns probabilistic aspects with applications to well-known Random Fields models which are representative for the corresponding stochastic Sobolev spaces. {The term "stochastic" in general indicates involvement of appropriate random elements. ) It assumes certain knowledge in general Analysis and Probability {Hilbert space methods, Schwartz distributions, Fourier transform) . I A very general description of the main problems considered can be given as follows. Suppose, we are considering a random field ~ in a region T ~ Rd which is associated with a chaotic (stochastic) source"' by means of the differential equation (*) in T. A typical chaotic source can be represented by an appropri­ ate random field"' with independent values, i. e. , generalized random function"' = ( cp, 'TJ), cp E C~(T), with independent random variables ( cp, 'fJ) for any test functions cp with disjoint supports. The property of having independent values implies a certain "roughness" of the ran­ dom field "' which can only be treated functionally as a very irregular Schwarz distribution. With the lack of a proper development of non­ linear analyses for generalized functions, let us limit ourselves to the 1 For related material see, for example, J. L. Lions, E.

Synopsis

This book considers some models described by means of partial differential equations and boundary conditions with chaotic stochastic disturbance. In a framework of stochastic partial differential equations an approach is suggested to generalize solutions of stochastic boundary problems. The main topic concerns probabilistic aspects with applications to the most well-known random fields models which are representative for the corresponding stochastic Sobolev spaces. This work assumes basic knowledge of general analysis and probability, such as Hilbert space methods, Schwartz distributions, and Fourier transforms. The volume should be of interest to researchers and postgraduate students whose work involves probability theory, stochastic processes and partial differential equations.