Detalhes bibliográficos
Ano de defesa: |
2014 |
Autor(a) principal: |
Nogueira, Aleksandro Costa
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Orientador(a): |
SANTANA, Ewaldo Eder Carvalho
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Banca de defesa: |
Barros Filho, Allan Kardek Duailibe
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Tipo de documento: |
Dissertação
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Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Universidade Federal do Maranhão
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Programa de Pós-Graduação: |
PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
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Departamento: |
Engenharia
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País: |
BR
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Palavras-chave em Português: |
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Palavras-chave em Inglês: |
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Área do conhecimento CNPq: |
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Link de acesso: |
http://tedebc.ufma.br:8080/jspui/handle/tede/509
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Resumo: |
This work has the objective to develop an analytical model that makes prediction of the behavior of the algorithm as a function of the design parameters (step adaptation, kernel function and its parameters).We use a non-quadratic function based on kernel, performing a nonlinear transformation of the input space filtering applied on line. Was developed and implemented in the system for adaptive filtering based on Kernel, which provides an analysis of the behavior of KRLS algorithm as well as its properties of convergence. It applies a kernel function in the cost function from the non-recursive quadratic function of an even power, which minimizes the error, defined as the expectation of the cumulative cost of actions taken along a sequence of steps. It appears that this approach allows the determination of the parameters of the problem with greater reliability and robustness and lower cost compared with traditional algorithms (RLS, KRLS, RNQ) . |