Constructive approximation to real function by wavelet neural networks

• Published in: Neural computing & applications Vol. 18; no. 8; pp. 883 - 889
• Main Authors: Muzhou, Hou, Xuli, Han, Yixuan, Gan
• Format: Journal Article
• Language: English
• Published: London Springer-Verlag 01.11.2009; Springer
• Subjects: Applied sciences; Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Computer science; control theory; systems; Data Mining and Knowledge Discovery; Exact sciences and technology; Fourier analysis; Image Processing and Computer Vision; Learning and adaptive systems; Mathematical analysis; Mathematics; Numerical analysis; Numerical analysis. Scientific computation; Original Article; Probability and Statistics in Computer Science; Real functions; Sciences and techniques of general use; Interpolation; Wavelet neural networks; Uniform approximation; Wavelets; Neural computation; Neuron; Error estimation; Wavelet transformation; Real function; Approximation by function; Continuous function; Neural network; Function approximation; Application

We present a type of single-hidden layer feed-forward wavelet neural networks. First, we give a new and quantitative proof of the fact that a single-hidden layer wavelet neural network with n  + 1 hidden neurons can interpolate n  + 1 distinct samples with zero error. Then, without training, we cons...