An Artificial Neuron Model with a Periodic Activation Function

Abstract

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.