skip to main content
Visitante
Meu Espaço
Minha Conta
Sair
Identificação
This feature requires javascript
Tags
Revistas Eletrônicas (eJournals)
Livros Eletrônicos (eBooks)
Bases de Dados
Bibliotecas USP
Ajuda
Ajuda
Idioma:
Inglês
Espanhol
Português
This feature required javascript
This feature requires javascript
Primo Search
Busca Geral
Busca Geral
Acervo Físico
Acervo Físico
Produção Intelectual da USP
Produção USP
Search For:
Clear Search Box
Search in:
Busca Geral
Or select another collection:
Search in:
Busca Geral
Busca Avançada
Busca por Índices
This feature requires javascript
This feature requires javascript
Interpretation of neuronal activity in neural networks
Gielen, C.C.A.M. ; Glasius, R. ; Komoda, A.
Neurocomputing (Amsterdam), 1996-01, Vol.12 (2-3), p.249-266
[Periódico revisado por pares]
Elsevier B.V
Texto completo disponível
Citações
Citado por
Exibir Online
Detalhes
Resenhas & Tags
Mais Opções
Nº de Citações
This feature requires javascript
Enviar para
Adicionar ao Meu Espaço
Remover do Meu Espaço
E-mail (máximo 30 registros por vez)
Imprimir
Link permanente
Referência
EasyBib
EndNote
RefWorks
del.icio.us
Exportar RIS
Exportar BibTeX
This feature requires javascript
Título:
Interpretation of neuronal activity in neural networks
Autor:
Gielen, C.C.A.M.
;
Glasius, R.
;
Komoda, A.
Assuntos:
Maximum likelihood estimation
;
Neural network
;
Population vector
;
Receptive field
É parte de:
Neurocomputing (Amsterdam), 1996-01, Vol.12 (2-3), p.249-266
Notas:
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
Descrição:
In this paper we will compare the performance of two techniques (the Maximum Likelihood Estimation (MLE) and the Population Vector (PV)) for estimating the interpretation of neuronal activity in a population of neurons. Although such a comparison has been made before, so far only homogeneous distributions of receptive fields have been investigated. Since the performance of both methods depends on the distribution of the receptive fields we have tested the performance for homogeneous and inhomogeneous distributions. The results demonstrate that in general the MLE method outperforms the Population Vector. However, the MLE method depends heavily on the shape of the receptive field properties of the neurons, which is not the case for the PV method. Moreover, the MLE method may give rise to artefactual results for inhomogeneous distributions of receptive fields. For the PV method the shape of the receptive field is not as important. Moreover, for the Population Vector the optimal width of the receptive field remains more or less constant when the decrease in density is small relative to the optimal width. In this case the information decreases proportionally with the density of receptive fields.
Editor:
Elsevier B.V
Idioma:
Inglês
This feature requires javascript
This feature requires javascript
Voltar para lista de resultados
This feature requires javascript
This feature requires javascript
Buscando em bases de dados remotas. Favor aguardar.
Buscando por
em
scope:(USP_PRODUCAO),scope:(USP_EBOOKS),scope:("PRIMO"),scope:(USP),scope:(USP_EREVISTAS),scope:(USP_FISICO),primo_central_multiple_fe
Mostrar o que foi encontrado até o momento
This feature requires javascript
This feature requires javascript