Quasi-Newton iteration algorithm for ICA and its application in VEP feature extraction / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 45-48, 2006.
Artigo
em Chinês
| WPRIM
| ID: wpr-309888
ABSTRACT
Some noises still exist in the single-trial averaged visual evoked potentials (VEP), so further extraction of the above results is of significance. Independent component analysis (ICA)can separate the sources from their mixtures and make the output statistically as independent as possible; it can remove noises effectively. In this paper, the principle, experiment analyses and results of ICA based on quasi-Newton iteration rule for VEP feature extraction are introduced, It is compared with the fixed-point FastICA algorithm. The experiment results show that the provided algorithm may reinforce signals effectively and extract distinct P300 from the single-trial averaged VEP. It is of good applicability.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Fisiologia
/
Algoritmos
/
Processamento de Sinais Assistido por Computador
/
Reconhecimento Automatizado de Padrão
/
Potenciais Evocados P300
/
Análise de Componente Principal
/
Potenciais Evocados Visuais
/
Métodos
Tipo de estudo:
Estudo prognóstico
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2006
Tipo de documento:
Artigo
Similares
MEDLINE
...
LILACS
LIS