旨在对Caianiello型离散神经元模型进行分析 ,由于这种模型具有动态阈值 ,它能够更加贴切地模拟生物神经元 .这种神经元模型恰为延迟动力系统 .我们所采用的方法是李雅普诺夫直接方法 .文中对各种不同情况得到了神经元系统平衡点的数量、位置的结果 .对每一种情况 ,我们还分析了这些平衡点的动态性质 ,理论分析和计算机仿真表明该神经元可以具有各种不同的特性 ,如全局吸引性、局部吸引性、不稳定性或振荡 The purpose of this paper is to analyze the Caianiello discrete neuron model, which has a dynamic threshold and is able to simulate the biological neuron more appropriately. This neuron model is precisely the delayed dynamical system. The method we adopted is Lyapunov Direct method, we get the number and location of equilibrium points of neuronal system in different situations.In each case, we also analyze the dynamic properties of these equilibrium points. Theoretical analysis and computer simulation show that the neurons can Has a variety of different properties, such as global attractiveness, local attractiveness, instability or oscillation