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Conditioning moments of singular measures for entropy maximization. II: numerical examples

Lookup NU author(s): Professor Mihai Putinar


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If moments of singular measures are passed as inputs to the entropy maximization procedure, the optimization algorithm might not terminate. The framework developed in [5] demonstrated how input moments of measures, on a broad range of domains, can be conditioned to ensure convergence of the entropy maximization. Here we numerically illustrate the developed framework on simplest possible examples: measures with onedimensional, bounded supports. Three examples of measures are used to numerically compare approximations obtained through entropy maximization with and without the conditioning step.

Publication metadata

Author(s): Budišić M, Putinar M

Editor(s): Hardin, DP; Lubinsky, DS; Simanek, BZ

Publication type: Book Chapter

Publication status: Published

Book Title: Modern Trends in Constructive Function Theory

Year: 2016

Volume: 661

Pages: 283-297

Print publication date: 01/01/2016

Acceptance date: 15/09/2015

Series Title: Contemporary Mathematics

Publisher: American Mathematical Society

Place Published: Providence, Rhode Island


DOI: 10.1090/conm/661/13288

Library holdings: Search Newcastle University Library for this item

ISBN: 9781470425340