@article{(Open Science Index):https://publications.waset.org/pdf/2132, title = {Comparison between Beta Wavelets Neural Networks, RBF Neural Networks and Polynomial Approximation for 1D, 2DFunctions Approximation}, author = {Wajdi Bellil and Chokri Ben Amar and Adel M. Alimi}, country = {}, institution = {}, abstract = {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 smooth 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. }, journal = {International Journal of Aerospace and Mechanical Engineering}, volume = {2}, number = {1}, year = {2008}, pages = {189 - 194}, ee = {https://publications.waset.org/pdf/2132}, url = {https://publications.waset.org/vol/13}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 13, 2008}, }