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Lipschitz optimization methods for fitting a sum of damped sinusoids to a series of observations

Gillard, J. W. and Kvasov, D. E. 2017. Lipschitz optimization methods for fitting a sum of damped sinusoids to a series of observations. Statistics and Its Interface 10 (1) , pp. 59-70. 10.4310/SII.2017.v10.n1.a6

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Abstract

A general nonlinear regression model is considered in the form of fitting a sum of damped sinusoids to a series of non-uniform observations. The problem of parameter estimation in this model is important in many applications like signal processing. The corresponding continuous optimization problem is typically difficult due to the high multiextremal character of the objective function. It is shown how Lipschitz-based deterministic methods can be well-suited for studying these challenging global optimization problems, when a limited computational budget is given and some guarantee of the found solution is required.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Mathematics
Subjects: Q Science > QA Mathematics
Publisher: International Press
ISSN: 1938-7989
Date of First Compliant Deposit: 28 September 2016
Date of Acceptance: 28 September 2016
Last Modified: 13 Mar 2020 10:20
URI: http://orca.cf.ac.uk/id/eprint/94969

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