Global and Local Optimization Algorithms for Optimal Signal Set Design

The problem of choosing an optimal signal set for non-Gaussian detection was reduced to a smooth inequality constrained mini-max nonlinear programming problem by Gockenbach and Kearsley. Here we consider the application of several optimization algorithms, both global and local, to this problem. The...

Descripción completa

Detalles Bibliográficos
Autor principal: Kearsley, Anthony J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: [Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology 2001
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4862810/
https://www.ncbi.nlm.nih.gov/pubmed/27500032
http://dx.doi.org/10.6028/jres.106.019
_version_ 1782431397106941952
author Kearsley, Anthony J.
author_facet Kearsley, Anthony J.
author_sort Kearsley, Anthony J.
collection PubMed
description The problem of choosing an optimal signal set for non-Gaussian detection was reduced to a smooth inequality constrained mini-max nonlinear programming problem by Gockenbach and Kearsley. Here we consider the application of several optimization algorithms, both global and local, to this problem. The most promising results are obtained when special-purpose sequential quadratic programming (SQP) algorithms are embedded into stochastic global algorithms.
format Online
Article
Text
id pubmed-4862810
institution National Center for Biotechnology Information
language English
publishDate 2001
publisher [Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology
record_format MEDLINE/PubMed
spelling pubmed-48628102016-08-05 Global and Local Optimization Algorithms for Optimal Signal Set Design Kearsley, Anthony J. J Res Natl Inst Stand Technol Article The problem of choosing an optimal signal set for non-Gaussian detection was reduced to a smooth inequality constrained mini-max nonlinear programming problem by Gockenbach and Kearsley. Here we consider the application of several optimization algorithms, both global and local, to this problem. The most promising results are obtained when special-purpose sequential quadratic programming (SQP) algorithms are embedded into stochastic global algorithms. [Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology 2001 2001-04-01 /pmc/articles/PMC4862810/ /pubmed/27500032 http://dx.doi.org/10.6028/jres.106.019 Text en https://creativecommons.org/publicdomain/zero/1.0/ The Journal of Research of the National Institute of Standards and Technology is a publication of the U.S. Government. The papers are in the public domain and are not subject to copyright in the United States. Articles from J Res may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
spellingShingle Article
Kearsley, Anthony J.
Global and Local Optimization Algorithms for Optimal Signal Set Design
title Global and Local Optimization Algorithms for Optimal Signal Set Design
title_full Global and Local Optimization Algorithms for Optimal Signal Set Design
title_fullStr Global and Local Optimization Algorithms for Optimal Signal Set Design
title_full_unstemmed Global and Local Optimization Algorithms for Optimal Signal Set Design
title_short Global and Local Optimization Algorithms for Optimal Signal Set Design
title_sort global and local optimization algorithms for optimal signal set design
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4862810/
https://www.ncbi.nlm.nih.gov/pubmed/27500032
http://dx.doi.org/10.6028/jres.106.019
work_keys_str_mv AT kearsleyanthonyj globalandlocaloptimizationalgorithmsforoptimalsignalsetdesign

Ejemplares similares