RBFNEURAL NETWORK FITTING MODEL TO VARIABLE- SEPARABLE FUNCTION AND ITS VC DIMENSION

A Radial Basis Function network fitting model to Variable-Separable function(VSRBF）is presented with its algorithm and its VC dimension is analyzed. VSRBF is a divide-and-cooperate system which is composed of several sub-RBF networks. Since VSRBF decomposes high dimensional model into low dimensional one, to compare with the conventional RBF, its system complexity is reduced remarkably as well as the faster converging speed. It is concluded that the VC dimension of VSRBF is less than that of the conventional RBF, and the experimental result shows that VSRBF performs advantageously comparing with the conventional RBF in high dimensional model.