Lyapunov exponent and chaotic area distribution of a chaotic neural network.
Chen Hong-ping · Journal of Zhejiang University(Sciences Edition) · 2004
Chaotic neural networks is a potential technique of information processing such as combinatorial optimization, information search, pattern identification, etc. The chaotic neural network model based on biological experiments proposed by Aihara et al. exhibits very complex dynamics and proves its dynamics to be dependent on its parameters. An algorithm to calculate the largest Lyapunov exponent of the chaotic neural network is presented. Based on the largest Lyapunov exponent, we investigated the chaotic area distribution of the neural network and discuss its dependence on the parameters. The results are significant for investigating chaotic dynamics and controlling chaos in the chaotic neural network.