Regularization of ill-posed problems: Optimal parameter choice in finite dimensions☆

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Abstract

We investigate a general class of regularization methods for ill-posed linear operator equations. An optimal a posteriori parameter choice strategy is developed for finite-dimensional approximations. The strategy is illustrated for a number of specific methods.

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Partially supported by the Austrian Fonds zur Förderung der wissenschaftlichen Forschung (project S32/03) and the U.S. National Science Foundation (Grant INT-8510037).

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On leave from Universität Linz, Austria; travel support from the Fullbright Commission is gratefully acknowledged.

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