Overview

Weighted Monte Carlo algorithms are useful when direct simulation techniques are inapplicable or ineffective in computer science and technology. This book presents methods which minimize the computer time and memory required in constructing statistical models for systems described by integral equations. Specific topics covered include the optimization of randomized algorithms for estimating probabilistic characteristics of equations with random parameters and applications; computational models for random fields and numerical simulations; vector Monte Carlo algorithms for solving systems of integral equations; and a special approach to the application of perturbation theory based on this method.

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9783540530053

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