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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Wavelet Neural Network Algorithms with Applications in Approximation Signals
verfasst von : Carlos Roberto Domínguez Mayorga, María Angélica Espejel Rivera, Luis Enrique Ramos Velasco, Julio Cesar Ramos Fernández, Enrique Escamilla Hernández
Erschienen in: Advances in Soft Computing
Verlag: Springer Berlin Heidelberg
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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.