Multi-frequency sinusoidal wave control in a chaotic neural network

Abstract

Brain waves are classified as gamma, beta, alpha, theta, and delta waves to quantify brain activity and can be approximated as sinusoidal waves of different frequencies. In this work, we use sinusoidal waves at two different frequencies to control chaos in a chaotic neural network (CNN) to explore the effect of multi-frequency sinusoidal waves in chaos control. We propose two methods to control chaos. In one, two sinusoidal wave signals are added to different groups of neurons. In the other, a control signal with a mixture of two sinusoidal waves with different frequencies is added to all neurons. The controlling dynamics differ in these two cases. A stable output sequence of the controlled CNN contains only one type of stored pattern and its reversed pattern, which are related to the initial pattern.