DocumentCode
1908671
Title
A feedforward neural network for the wavelet decomposition of discrete time signals
Author
Marcos, Sylvie ; Benidir, Messaoucd
Author_Institution
Lab. des Signaux et Syst., E.S.E., Gif-sur-Yvette, France
fYear
1993
fDate
6-9 Sep 1993
Firstpage
475
Lastpage
484
Abstract
A feedforward neural network with sigmoidal activation functions is proposed to perform the wavelet decomposition of a discrete time signals. The proposed network is made of two parts, the main network and the auxiliary network. The learning of the auxiliary network is achieved off-line, in a prior phase, in order to identify the desired wavelet. This identification is possible due to the properties of a neural network with one hidden layer to approximate any continuous function with a desired accuracy
Keywords
feedforward neural nets; signal processing; wavelet transforms; continuous function; discrete time signals; feedforward neural network; identification; sigmoidal activation functions; wavelet decomposition; Continuous wavelet transforms; Discrete wavelet transforms; Feedforward neural networks; Fourier transforms; Frequency; Multiresolution analysis; Neural networks; Signal analysis; Signal processing; Wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Processing [1993] III. Proceedings of the 1993 IEEE-SP Workshop
Conference_Location
Linthicum Heights, MD
Print_ISBN
0-7803-0928-6
Type
conf
DOI
10.1109/NNSP.1993.471840
Filename
471840
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