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Linear best approximation using a class ofk-majorl p norms

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Abstract

Consideration is given to problems of linear best approximation using a variant of the usuall p norms referred to ask-majorl p norms, for the cases when 1<p<∞. The underlying problem is the minimization of a piecewise smooth function. Best approximations are characterized, and a descent algorithm is developed.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Dundee, DD1 4HN, Dundee, Scotland, UK

    G. A. Watson

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  1. G. A. Watson
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Communicated by C. Brezinski

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Watson, G.A. Linear best approximation using a class ofk-majorl p norms. Numer Algor 8, 135–146 (1994). https://doi.org/10.1007/BF02145701

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  • DOI: https://doi.org/10.1007/BF02145701

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