On selecting typical samples in EMG pattern classification / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 271-274, 2007.
Artigo
em Chinês
| WPRIM
| ID: wpr-357718
ABSTRACT
As is well known that the quality of training samples directly influence the recognizing ability of neural network. In this paper, we introduce a method for solving the problem of how to classify the pattern of forearm by obtaining typical samples. At first, the original samples were pretreated by using the membership class function that can improve the quality of cluster sample. Then, the center of clustering could be gained by using the method of clustering and the typical sample was obtained. Based on this method, we can get the typical sample that corresponds with the movements of stretch of arm and fold of arm. We can make them as the training sample of the BP network to classify the pattern of forearm. The experiment indicates that this measure can improve the point of identification.
Texto completo:
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Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Fisiologia
/
Algoritmos
/
Processamento de Sinais Assistido por Computador
/
Reconhecimento Automatizado de Padrão
/
Análise por Conglomerados
/
Redes Neurais de Computação
/
Eletromiografia
/
Antebraço
/
Métodos
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2007
Tipo de documento:
Artigo
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