Memorizing and regenerating spatiotemporal patterns with a structured recurrent neural network
Yisheng Li, Yoshikazu Miyanaga, Koji Tochinai · Electronics and Communications in Japan (Part III Fundamental Electronic Science) · 1996
Abstract A local connected recurrent neural network with the ability to memorize and regenerate some nonlinear complex dynamics is proposed in this paper and a new learning algorithm for this network is also developed. the network, constructed of adaptive oscillating modules, is easily applied to the realization of nonlinear dynamics. the module consists of two simple neuron nodes with recurrent connections. the new learning algorithm can independently train each module with suitable speed for given input data. the network size is also adaptively determined during the learning process. This network also has a suitable structure of a parallel VLSI system. Finally, some simulation results are given to verify the effectiveness on the proposed network structure and the learning algorithm.