@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},
	}