Adaptive optimization with constraints: Convergence and oscillatory behaviour

Fernando J. Coito, João M. Lemos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

The problem of adaptive minimization of globally unknown functionals under constraints on the independent variable is considered in a stochastic framework. The CAM algorithm for vector problems is proposed. By resorting to the ODE analysis for analysing stochastic algorithms and singular perturbation methods, it is shown that the only possible convergence points are the constrained local minima. Simulation results in 2 dimensions illustrate this result.

Original languageEnglish
Title of host publicationPATTERN RECOGNITION AND IMAGE ANALYSIS, PT 2, PROCEEDINGS
EditorsJ. S. Marques, N. Perez de la Blanca, P. Pina
Place of PublicationBerlin, Heidelberg
PublisherSpringer Verlag
Pages19-26
Number of pages8
Volume3523
EditionII
ISBN (Print)3-540-26154-0
Publication statusPublished - 30 Sep 2005
EventSecond Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2005 - Estoril, Portugal
Duration: 7 Jun 20059 Jun 2005

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
Volume3523
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceSecond Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2005
CountryPortugal
CityEstoril
Period7/06/059/06/05

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