A Method Which Generates Splines in H-Locally Convex Spaces and Connections with Vectorial Optimization

A Method Which Generates Splines in H-Locally Convex Spaces and Connections with Vectorial... In this research paper we present a modality for generating splines in H-locally convex spaces which allows us to solve some problems of best approximation by linear subspaces of spline functions in these spaces. In this way one shows that the elements of best vectorial approximation coincide with the spline functions introduced by us in a previous research work. These splines are also the only elements of best simultaneous approximation by their generated linear subspaces with respect to any family of seminorms which induces the H-locally convex topology and, consequently, they are the only solutions for some frequent strong and vectorial optimization programs. Moreover, as we shall see in the numerical examples, our construction leads to discover orthogonal decompositions for H-locally convex spaces which, in general, are difficult to be identified. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Positivity Springer Journals

A Method Which Generates Splines in H-Locally Convex Spaces and Connections with Vectorial Optimization

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 1998 by Kluwer Academic Publishers
Subject
Mathematics; Fourier Analysis; Operator Theory; Potential Theory; Calculus of Variations and Optimal Control; Optimization; Econometrics
ISSN
1385-1292
eISSN
1572-9281
D.O.I.
10.1023/A:1009763323140
Publisher site
See Article on Publisher Site

Abstract

In this research paper we present a modality for generating splines in H-locally convex spaces which allows us to solve some problems of best approximation by linear subspaces of spline functions in these spaces. In this way one shows that the elements of best vectorial approximation coincide with the spline functions introduced by us in a previous research work. These splines are also the only elements of best simultaneous approximation by their generated linear subspaces with respect to any family of seminorms which induces the H-locally convex topology and, consequently, they are the only solutions for some frequent strong and vectorial optimization programs. Moreover, as we shall see in the numerical examples, our construction leads to discover orthogonal decompositions for H-locally convex spaces which, in general, are difficult to be identified.

Journal

PositivitySpringer Journals

Published: Oct 14, 2004

References

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