BDBComp
Parceria:
SBC
Echo State Incremental Gaussian Mixture Network for Spatio-Temporal Pattern Processing

Rafael C. PintoPaulo M. EngelMilton R. Heinen

This work introduces a novel neural network algorithm for online spatio-temporal pattern processing, called Echo State Incremental Gaussian Mixture Network (ESIGMN). The proposed algorithm is a hybrid of two state- of-the-art algorithms: the Echo State Network (ESN), used for spatio-temporal pattern processing, and the Incremental Gaussian Mixture Network (IGMN), ap- plied to aggressive learning in online tasks. The algorithm is compared against the conventional ESN in order to highlight the advantages of the IGMN ap- proach as a supervised output layer.

http://www.lbd.dcc.ufmg.br/colecoes/enia/2011/0019.pdf

Caso o link acima esteja inválido, faça uma busca pelo texto completo na Web: Buscar na Web

Biblioteca Digital Brasileira de Computação - Contato: bdbcomp@lbd.dcc.ufmg.br
     Mantida por:
LBD