Modified Hebbian algorithm for analog VLSI neural network implementation

Hiroyuki Wasaki, Yoshihiko Horio, Shogo Nakamura

研究成果: Article査読


Various studies on learning rules for neural networks have been done However, most of those do not consider the hardware implementation, which is a great drawback in the LSI implementation of neural networks with learning capability. From such a viewpoint, this paper proposes a self organizing learning rule by modifying the Hebbian learning rule. This rule can be implemented easily on an analog VLSI chip as an on-chip learning rule. The self-organizing ability of the system is verified by simulation experiments. It is shown from the experiment that the learning speed is improved by a factor of 2 to 3, and it is possible to avoid the sudden termination of the learning and the divergence of the synaptic weights.

ジャーナルElectronics and Communications in Japan, Part III: Fundamental Electronic Science (English translation of Denshi Tsushin Gakkai Ronbunshi)
出版ステータスPublished - 1993 11 1

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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