Initialization by selection for wavelet network training

DOI10.1016/S0925-2312(00)00295-2zbMath1009.68843OpenAlexW2085686600MaRDI QIDQ1852088

Gérard Dreyfus, Yacine Oussar

Publication date: 9 January 2003

Published in: Neurocomputing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0925-2312(00)00295-2

zbMATH Keywords

TrainingInitializing parametersNonlinear static modelingWavelet networks

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies and applications (68U99)

Related Items (10)

Comparative analysis of adaptive neurofuzzy control techniques for full car active suspension system ⋮ Forward and backward least angle regression for nonlinear system identification ⋮ A systematic investigation of a neural network for function approximation ⋮ Nonlinear system identification using quasi-ARX RBFN models with a parameter-classified scheme ⋮ Self-adaptive vibration control of simply supported beam under a moving mass using self-recurrent wavelet neural networks via adaptive learning rates ⋮ Ultra-high dimensional variable screening via Gram-Schmidt orthogonalization ⋮ Artificial wavelet neuro-fuzzy model based on parallel wavelet network and neural network ⋮ Wavelet neural networks: a practical guide ⋮ Functional variable selection via Gram–Schmidt orthogonalization for multiple functional linear regression ⋮ Modeling and Forecasting CAT and HDD Indices for Weather Derivative Pricing

This page was built for publication: Initialization by selection for wavelet network training