The average-case analysis of numerical problems is the counterpart of the more traditional worst-case approach. The analysis of average error and cost leads to new insight on numerical problems as well as to new algorithms. The book provides a survey of results that were mainly obtained during the last 10 years and also contains new results. The problems under consideration include approximation/optimal recovery and numerical integration of univariate and multivariate functions as well as zero-finding and global optimization. Background material, e.g. on reproducing kernel Hilbert spaces and random fields, is provided. TOC:Introduction; Linear Problems: Definitions and a Classical Example; Second-Order Results for Linear Problems; Integration and Approximation of Univariate Functions; Linear Problems for Univariate Functions with Noisy Data; Integration and Approximation of Multivariate Functions; Nonlinear Methods for Linear Problems; Nonlinear Problems.
i.d.R. innert 5-10 Tagen versandfertig
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