IIIE 20352
INSTITUTO DE INVESTIGACIONES EN INGENIERIA ELECTRICA "ALFREDO DESAGES"
Unidad Ejecutora - UE
artículos
Título:
Dynamical Functional Artificial Neural Network: Use of Efficient Piecewise Linear Function
Autor/es:
JOSE LUIS FIGUEROA; JUAN EDMUNDO COUSSEAU
Revista:
LATIN AMERICAN APPLIED RESEARCH
Editorial:
Universidad Nacional del Sur
Referencias:
Lugar: Bahia Blanca; Año: 2008 vol. 38 p. 187 - 193
ISSN:
0327-0793
Resumen:
A nonlinear adaptive time series predictor has been developed using a new type of piecewise linear (PWL) network for its underlying model structure. The PWL Network is a D-FANN (Dynamical Functional Artificial Neural Network) the activation functions of which are piecewise linear. The new realization is presented with the associated training algorithm. Properties and characteristics are discussed. This network has been successfully used to model and predict an important class of highly dynamic and non-stationary signals, namely speech signals.
