The Necessity of Introducing Chaos into Artificial Neural Network
Yan Pingfa · Beijing shengwu yixue gongcheng · 2002
Based on results of Freeman′s physiological and simulation experiments, we summarized Freeman and Tsuda′s explanation of chaos dynamics in bio neural network. From point of views of information flow, we discuss the necessity of existence of chaos in bio neural system, we discuss the potential information processing capability of models in ANN, where chaos mechanism has been introduced. We point out that, when there is input from outside world, the reaction of a cognition system is a change of characteristics of it′s dynamics behavior, not only static output value. It is also suggested that neural networks with characteristics of chaotic dynamics have ability of pattern classification and pattern interpretation simultaneously. This combination comes from characteristics of chaos dynamics of the system, describing the role of chaos in pattern recognition. We point out some advantages, comparing our model with those traditional neural network models like ART. Part of the conclusions were proved during simulation experiments.