Comparison Between Beta Wavelets Neural Networks, Rbf Neural Networks And Polynomial Approximation For 1D, 2Dfunctions Approximation

Wajdi Bellil, Chokri Ben Amar, Adel M. Alimi
2008 Zenodo  
This paper proposes a comparison between wavelet neural networks (WNN), RBF neural network and polynomial approximation in term of 1-D and 2-D functions approximation. We present a novel wavelet neural network, based on Beta wavelets, for 1-D and 2-D functions approximation. Our purpose is to approximate an unknown function f: Rn - R from scattered samples (xi; y = f(xi)) i=1....n, where first, we have little a priori knowledge on the unknown function f: it lives in some infinite dimensional
more » ... oth function space and second the function approximation process is performed iteratively: each new measure on the function (xi; f(xi)) is used to compute a new estimate f as an approximation of the function f. Simulation results are demonstrated to validate the generalization ability and efficiency of the proposed Beta wavelet network.
doi:10.5281/zenodo.1056513 fatcat:bxceneois5bqtbrnyjbdbunpb4