Abstract
In this study, a revised radial basis function (RBF) network is proposed and applied to the identification problems of the nonlinear system and the interactive art system. In the revised RBF network, the structural parameters such as means and variances of the radial basis functions in the neurons are determined automatically and so revised RBF network can be easily applied to the practical complex problems such as the interactive art system. The interactive art system outputs the art expressions such as the sound and graphics using the artificial sensibility surfaces that are identified using the revised RBF network.
