Training wavelet networks for nonlinear dynamic input-output modeling

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In the framework of nonlinear process modeling, we propose training algorithms for feedback wavelet networks used as nonlinear dynamic models. An original initialization procedure is presented, that takes the locality of the wavelet functions into account. Results obtained for the modeling of several processes are presented; a comparison with networks of neurons with sigmoidal functions is performed.

Yacine Oussar, Isabelle Rivals, Léon Person

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IJON 1998 | Nonlinear Dynamic Models | Nonlinear Process | Original Initialization Procedure |

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Added	22 Dec 2010
Updated	22 Dec 2010
Type	Journal
Year	1998
Where	IJON
Authors	Yacine Oussar, Isabelle Rivals, Léon Personnaz, Gérard Dreyfus

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Training wavelet networks for nonlinear dynamic input-output modeling

IJON 1998 | Nonlinear Dynamic Models | Nonlinear Process | Original Initialization Procedure |

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