时滞神经网络稳定性、分岔与混沌的研究进展

时滞广泛存在于神经网络中，从非线性动力学的角度对时滞神经网络系统的研究进展作一综述，内容包括时滞神经网络系统的特点、研究方法、神经网络动力学的热点问题的研究进展以及亟待解决的问题等。由于时滞神经网络的演化趋势不仅依赖于系统的当前状态，还依赖于系统的过去某一时刻或若干时刻的状态，其运动方程要用泛函微分方程来描述，解的空间是无穷维的，因此，时滞神经网络的动态行为是非常复杂的。

Survey on Stability, Bifurcation and Chaos in Delayed Neural Networks

From the viewpoint of nonlinear dynamics, this review outlines the recent advances as well as some open problems in the study of neural networks with time delays, an important class of delayed systems in various neural network models. The survey includes three aspects as fellows: the dynamic features, available approaches and advances in research on most attractive problems. The evolution of a delayed neural network depends not only on the current state of the systems but also on previous ones. Hence, a delayed neural network should be modeled by a functional differential equation, the solution space of which is of infinite dimensions. Therefore, the dynamical behavior of delayed neural networks is very complex.