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Random Fields and Stochastic Partial Differential Equations

Random Fields and Stochastic Partial Differential Equations

Y. Rozanov

132,79 €
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Editorial:
Springer Nature B.V.
Año de edición:
1998
Materia
Probabilidad y estadística
ISBN:
9780792349846

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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.

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