Department of Mathematics;
Research Center for Nonlinear Science and Laboratory of Mathematics for Nonlinear Science;
Fudan University;
Shanghai 200433;
P.R.China;
Department of Mathematics;
Research Center for Nonlinear Science and Laboratory of Mathematics for Nonlinear Science;
Fudan University;
Shanghai 200433;
P.R.Chinat was theoretically proved that one-dimensional transiently chaotic neural networks have chaotic structure in sense of Li-Yorke theorem with some given assumptions using that no division implies chaos. In particular;
it is further derived sufficient conditions for the existence of chaos in sense of Li- Yorke theorem in chaotic neural network;
which leads to the fact that Aihara has demonstrated by numerical method. Finally;
an example and numerical simulation are shown to illustrate and reinforce the previous theory.;
混沌; 不规则神经网络; Li-Yorke定理; 数值模拟;