在人工神经网络中引入混沌的必要性  

The Necessity of Introducing Chaos into Artificial Neural Network

作　　者：吕正东[1] 阎平凡[1] 

机构地区：[1]清华大学自动化系,100084

出　　处：《北京生物医学工程》2002年第3期207-211,共5页Beijing Biomedical Engineering

基　　金：国家自然科学基金第 69875 0 11号资助

摘　　要：本文从Freeman的生理学实验和仿真实验的结果出发 ,综合了Freeman和Tsuda对生物神经网络中混沌动力学的解释 ,从信息流动的角度论述了在生物神经网络中混沌存在的必要性和引入混沌机制的人工神经网络模型所具有的信息处理的潜力 ,指出认知系统对外界输入的反应是其动力学行为性质的改变而不仅是静态的数值输出。并认为具有混沌动力学性质的神经网络应同时具有模式分类器和解释器的双重作用。这一结合来自于系统的混沌动力性质。描述了混沌在模式识别中的作用 ,指出了其相对ART等传统神经网络模型的一些优势。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.

关 键 词：必要性 神经网络 混沌 模式识别 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]