AN ARTIFICIAL NEURON MODEL WITH A PERIODIC ACTIVATION FUNCTION

被引:35
作者
NAKAGAWA, M
机构
[1] Department of Electrical Engineering, Faculty of Engineering, Nagaoka University of Technology, Nagaoka 940-21
关键词
CHAOS NEURON; PERIODIC MAPPING; CHAOTIC RETRIEVAL; ASSOCIATIVE MEMORY;
D O I
10.1143/JPSJ.64.1023
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In this paper we shall propose a novel chaos neuron model with a periodic activation function and investigate the dynamic properties in a chaotic memory retrieval mode. The present artificial neuron model is characterized by a sinusoidal activation function. It is elucidated that the present neural network has an ability of the dynamic memory retrievals beyond the conventional chaotic model with such a monotonous mapping as a sigmoid function. This advantage is considered to result from the nonmonotonous property of the analogue periodic mapping which may be accompanied with a chaotic behaviour of the neurons. It is also found that the present analogue neuron model has a relatively larger memory capacity than the conventional association model even for the case of the monotonous mapping as a special case.
引用
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页码:1023 / 1031
页数:9
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