Adaptive Pointing Theory (APT) Artificial Neural Network


Autoria(s): Al-Rawi, Kamal; Gonzalo Martín, Consuelo
Data(s)

01/05/2014

Resumo

The choice value and the testing process against the vigilance parameter, characteristic of ART Neural Network, are merged. Only, a single unique test is required to determine if a committed category node can represent the current input or not. Advantages of APT over ART are: 1-Avoid testing every committed category node before deciding to train a committed category node or a new node must be committed, 2-The vigilance parameter is fixed during training, and 3-The choice value parameter is eliminated.

Formato

application/pdf

Identificador

http://oa.upm.es/35627/

Idioma(s)

spa

Publicador

E.T.S. de Ingenieros Informáticos (UPM)

Relação

http://oa.upm.es/35627/1/35627_INVE_MEM_2014.pdf

http://www.ijcce.org/

info:eu-repo/semantics/altIdentifier/doi/10.7763/IJCCE.2014.V3.322

Direitos

http://creativecommons.org/licenses/by-nc-nd/3.0/es/

info:eu-repo/semantics/openAccess

Fonte

International Journal of Computer and Communication Engineering, ISSN 2010-3743, 2014-05, Vol. 3, No. 3

Palavras-Chave #Química
Tipo

info:eu-repo/semantics/article

Artículo

PeerReviewed