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Zbl 0609.60072
Adomian, George
Nonlinear stochastic operator equations. (English)
[B] Orlando etc.: Academic Press, Inc. (Harcourt Brace Jovanovich, Publishers). XV, 287 p. {\$} 64.50; \sterling 54.00 (1986). ISBN 0-12-044375-9

The author expresses his basic principle as follows: "It is not always wise to follow overzealously the footsteps of the masters". \par The book contains a really new and original method for solving nonlinear (and linear as a particular case) stochastic (and deterministic as a particular case) equations of general type (differential, algebraic, etc.). This is the so called decomposition method involving the $A\sb n$- polynomials-technique which in brief could be explained as follows: Assume a function f is to be found which obeys the equation $Lf=Nf$, where L is an invertible linear operator and N is a nonlinear one. We decompose f as $f=f\sb 0+f\sb 1+..$. and write Nf as $Nf=A\sb 0(f\sb 0)+A\sb 1(f\sb 0,f\sb 1)+...+A\sb n(f\sb 0,f\sb 1,...,f\sb n)+...$, where $A\sb n$ for $n\ge 0$ is a polynomial of degree n. Then $f\sb n$ is obtained according to the following recursive scheme: $Lf\sb 0=0$ and $f\sb n=L\sp{-1}A\sb{n-1}(f\sb 0,...,f\sb{n-1})$ for $n\ge 1$. The calculation of the $A\sb n$-polynomials is made explicit in the most important cases of nonlinear operators N. When one deals with a differential equation L is a differential operator and its inversion means to calculate the corresponding Green's function. This problem is broadly discussed. \par The author proposes a principally new treatment of deterministic and stochastic problems in which both cases are considered simultaneously. It should be pointed out that such an approach contradicts to the tradition. However it might be that in this joint treatment "stochastic differentiation" is loosing its typical nature. The author illustrates his new theory with many examples and comparisons with traditional methods. Some general and very interesting remarks concerned with the exploration of the present computer generation are given. The convergence question is also considered and answered at least for the most important cases of appearing nonlinearities. \par The book is easy to read meaning that it is within the grasp of any graduate student in mathematics. However, because of its principally new approach, it addresses researchers mainly. It is apparent that the author has used successfully his method for solving important practical problems. The book really deserves to be noticed by anyone whose main topics are equations (stochastic or deterministic) from both - practical and purely theoretic point of view. Finally the reader can hardly avoid the impression that the author is a master too.
[O.Enchev]

MSC 2000:: *60H25 Random operators, etc.
60-02 Research monographs (probability theory)
34A34 Nonlinear ODE and systems, general
34F05 ODE with randomness
35R60 PDE with randomness
60H10 Stochastic ordinary differential equations
60H15 Stochastic partial differential equations

Keywords: decomposition method; Green's function

Cited in: Zbl 1087.65528 Zbl 1083.92024 Zbl 1083.92021 Zbl 1054.92025 Zbl 1048.92013 Zbl 0828.65081 Zbl 0808.65073 Zbl 0802.65122 Zbl 0772.34009 Zbl 0772.34015 Zbl 0765.34005 Zbl 0767.35016 Zbl 0755.92005 Zbl 0719.93041 Zbl 0721.41043 Zbl 0713.35004 Zbl 0645.65040 Zbl 0631.65119 Zbl 0693.35068 Zbl 0649.70006 Zbl 0641.35002 Zbl 0624.60079 Zbl 0623.60084 Zbl 0616.65084 Zbl 0616.65054 Zbl 0616.65053

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