Wavelet Neural Network Algorithms with Applications in Approximation Signals

被引：0

作者：

Dominguez Mayorga, Carlos Roberto ^{[1
]}

Espejel Rivera, Maria Angelica

Ramos Velasco, Luis Enrique ^{[2
]}

Ramos Fernandez, Julio Cesar ^{[3
,4
]}

Escamilla Hernandez, Enrique ^{[3
]}

机构：

[1] Univ Politecn Metropolitana Hidalgo, Camerino Mendoza 318, Pachuca 42040, Hgo, Mexico

[2] Univ Salle Pachuca, Campus La Concepcion, Hidalgo, Mexico

[3] Univ Autonoma del Estado Hidalgo, Ctr Investigacion Tecnologias Inform Syst, Hidalgo, Mexico

[4] Univ Politenica Pachuca, Carretera Pachuca Cd, Hidalgo, Mexico

来源：

ADVANCES IN SOFT COMPUTING, PT II | 2011年 / 7095卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we present algorithms which are adaptive and based on neural networks and wavelet series to build wavenets function approximators. Results are shown in numerical simulation of two wavenets approximators architectures: the first is based on a wavenet for approach the signals under study where the parameters of the neural network are adjusted online, the other uses a scheme approximators with an IIR filter in the output of wavenet, which helps to reduce convergence time to a minimum time desired.

引用

页码：374 / +

页数：3

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