NDLI: Convergência Do Erro De Predição Em Identificação Neural Sujeita A Distúrbios E Parâmetros Variantes No Tempo

Content Provider	Semantic Scholar
Author	Vargas, José A. R. Hemerly, Elder Moreira
Copyright Year	2005
Abstract	Resumo – Neste artigo é proposto um algoritmo para identificação neural de sistemas contínuos não-lineares incertos com parâmetros variantes no tempo e sujeitos a distúrbios. Prova-se, via argumentos usuais de Lyapunov e uma técnica de limitação adaptativa (adaptive bounding technique), que o erro de predição converge para zero, inclusive na presença de erros de aproximação e distúrbios, enquanto os outros erros associados permanecem limitados. Simulações são apresentadas para ilustrar a aplicação e desempenho do algoritmo proposto.
Starting Page	84
Ending Page	97
Page Count	14
File Format	PDF HTM / HTML
DOI	10.21528/LNLM-vol3-no2-art4
Volume Number	3
Alternate Webpage(s)	http://abricom.org.br/wp-content/uploads/sites/4/2016/07/vol3-no2-art4.pdf
Alternate Webpage(s)	https://doi.org/10.21528/LNLM-vol3-no2-art4
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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