现在研究神经网络的人很多,但主要是人工神经网络。最近,有几个实验室分析了健康人的脑电图,发现其中存在混沌的证据;混沌也会是神经系统的正常特征。其实,尤其在一个单独的生物神经元中,可以在实验上观察到混沌性态,而这是一般人工神经元所没有的。本文介绍一种单独神经元的模型,它能够定性地描写实验观察到的混沌响应。一、神经元的非线性动力学模拟生物神经元动态的历史要追溯到早期的一些著名模型,例如MoCulloch-Pitts神经元(1943)和 Nowadays there are many people studying neural networks, but mainly artificial neural networks. Recently, several laboratories have analyzed the EEG of healthy people and found evidence of chaos in them; chaos can also be a normal feature of the nervous system. In fact, especially in a single biological neuron, chaotic behavior can be observed experimentally, which is not found in normal artificial neurons. This article presents a model of a single neuron that characterizes the chaotic response experimentally observed. First, the nonlinear dynamics of neurons to simulate the history of biological neurons go back to some of the early well-known models, such as MoCulloch-Pitts neurons (1943) and