A wavelet neural network with network optimizing function
Kunizaku Kobayashi, Toyoshi Torioka, Nobuo Yoshida · Systems and Computers in Japan · 1995
Abstract A new mapping network combining wavelets and neural networks is proposed. The proposed network has three major characteristics, namely, self‐construction of neural networks, partial retrieval of the approximate mapping, and efficient learning. The network learning algorithm can be divided roughly into the self‐construction process and the error minimization process. In the first process, hidden units are appended serially in such a way that the network structure sufficiently approximates the approximation target. Simultaneously, network parameters are updated by competitive learning. In the second process, network parameters are updated by a localized backpropagation algorithm until the desired approximation accuracy is attained. The effectiveness of the proposed network is demonstrated through computer simulations.