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An adaptive learning algorithm for a wavelet neural network
Author(s) -
Bodyanskiy Yevgeniy,
Lamonova Nataliya,
Pliss Iryna,
Vynokurova Olena
Publication year - 2005
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/j.1468-0394.2005.00314.x
Subject(s) - computer science , wavelet , smoothing , artificial neural network , artificial intelligence , wake sleep algorithm , algorithm , tracking (education) , pattern recognition (psychology) , computer vision , generalization error , psychology , pedagogy
An optimal online learning algorithm of a wavelet neural network is proposed. The algorithm provides not only the tuning of synaptic weights in real time, but also the tuning of dilation and translation factors of daughter wavelets. The algorithm has both tracking and smoothing properties, so the wavelet networks trained with this algorithm can be efficiently used for prediction, filtering, compression and classification of various non‐stationary noisy signals.