Multilayer neural network with on-chip learning based on frequency-modulated pulse signals and voting neurons
Hiroomi Hikawa · Electronics and Communications in Japan (Part III Fundamental Electronic Science) · 2000
In this paper, a pulse-mode multilayer neural network with on-chip learning is proposed. The neuron unit uses voting circuit as a nonlinear adder to improve the nonlinear activation function. Moreover, the voting circuit is modified to have adjustable nonlinear characteristic. As the signal level is expressed by the frequency, synapse multipliers are realized by simple frequency converters. The back propagation algorithm is used for the on-chip learning. The proposed multilayer neural network is implemented on field programmable gate array (FPGA), and various experiments are conducted. The results show that the proposed neuron has adjustable nonlinear function. The learning capability of the proposed network is also verified by the experiments. © 2000 Scripta Technica, Electron Comm Jpn Pt 3, 84(1): 32–42, 2001