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Comparison Between Beta Wavelets Neural Networks, Rbf Neural Networks And Polynomial Approximation For 1D, 2Dfunctions Approximation
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
doi:10.5281/zenodo.1056513
fatcat:bxceneois5bqtbrnyjbdbunpb4