Chaotic convergence of the decision-directed blind equalization algorithm

dc.creatorSoriano, DC
dc.creatorNadalin, EZ
dc.creatorSuyama, R
dc.creatorRomano, JMT
dc.creatorAttux, R
dc.date2012
dc.dateDEC
dc.date2014-07-30T16:51:44Z
dc.date2015-11-26T17:54:18Z
dc.date2014-07-30T16:51:44Z
dc.date2015-11-26T17:54:18Z
dc.date.accessioned2018-03-29T00:37:55Z
dc.date.available2018-03-29T00:37:55Z
dc.identifierCommunications In Nonlinear Science And Numerical Simulation. Elsevier Science Bv, v. 17, n. 12, n. 5097, n. 5109, 2012.
dc.identifier1007-5704
dc.identifierWOS:000307104000058
dc.identifier10.1016/j.cnsns.2012.05.015
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/62734
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/62734
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1290753
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionClassically, adaptive equalization algorithms are analyzed in terms of two possible steady state behaviors: convergence to a fixed point and divergence to infinity. This twofold scenario suits well the modus operandi of linear supervised algorithms, but can be rather restrictive when unsupervised methods are considered, as their intrinsic use of higher-order statistics gives rise to nonlinear update expressions. In this work, we show, using different analytical tools belonging to dynamic system theory, that one of the most emblematic and studied unsupervised approaches - the decision-directed algorithm - is potentially capable of presenting behaviors, like convergence to limit-cycles and chaos, that transcend the aforementioned dichotomy. These results also indicate theoretical possibilities concerning step-size selection and initialization. (C) 2012 Elsevier B.V. All rights reserved.
dc.description17
dc.description12
dc.description5097
dc.description5109
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.languageen
dc.publisherElsevier Science Bv
dc.publisherAmsterdam
dc.publisherHolanda
dc.relationCommunications In Nonlinear Science And Numerical Simulation
dc.relationCommun. Nonlinear Sci. Numer. Simul.
dc.rightsfechado
dc.rightshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.sourceWeb of Science
dc.subjectBlind equalization
dc.subjectChaotic behavior
dc.subjectDecision-directed algorithm
dc.subjectDynamical systems
dc.subjectAdaptive Equalizers
dc.titleChaotic convergence of the decision-directed blind equalization algorithm
dc.typeArtículos de revistas


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