A piecewise linear dynamical functional artificial neural network (PWL-DFANN) for nonlinear adaptive time series prediction

Author

Figueroa, J.L. ; Cousseau, J.E. ; De Figueiredo, R. J P

Author_Institution

Dept. of Electr. Eng., Univ. Nacional del Sur, Bahia Blanca, Argentina

Volume

1

fYear

2002

fDate

6/24/1905 12:00:00 AM

Abstract

A nonlinear adaptive time series predictor has been developed using a PWL-DFANN network (piecewise linear dynamical functional artificial neural network) for its underlying model structure. This network is so called because it is a D-FANN the activation functions of which are piecewise linear. The network has been successfully used to model and predict an important class of highly dynamic and nonstationary signals, namely speech signals.

Keywords

adaptive signal processing; neural nets; piecewise linear techniques; speech processing; time series; PWL-DFANN; activation functions; model structure; nonlinear adaptive time series prediction; nonstationary signals; piecewise linear dynamical functional artificial neural network; speech signals; Adaptive filters; Artificial neural networks; Discrete cosine transforms; Ear; Finite impulse response filter; Piecewise linear techniques; Predictive models; Recurrent neural networks; Signal processing; Speech processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2002. ISCAS 2002. IEEE International Symposium on

Print_ISBN

0-7803-7448-7

Type

conf

DOI

10.1109/ISCAS.2002.1009769

Filename

1009769