作　　者： ; ;

机构地区： 江南大学通信与控制工程学院

出　　处： 《自动化学报》 2009年第1期77-84,共8页

摘　　要： 通过构造适当的Lyapunov泛函、利用M矩阵性质和不等式技巧,在不要求神经网络激励函数的有界性、单调性和可微性弱保守条件下,探讨了一类具有分布参数和分布时滞的Cohen-Grossberg动态神经网络周期解的存在性和指数稳定性问题,提出了一系列充分性判据来确保这类同时具有分布参数和分布时滞神经网络周期解的存存性和指数稳定性,并通过几个沣解以及与其他文献结果进行比较说明了该方法的优越性.最后,给出了数值例子和计算机仿真米验证这一理论的有效性. In this paper, the existence and exponential stability problems of periodic solutions are discussed for a class of Cohen-Grossberg dynamic neural networks with distributed delays and reaction-diffusion terms. Without assuming the boundedness, monotonicity and differentiability of the activation functions, some sufficient conditions are obtained to guarantee the existence and the global exponential stability of periodic solutions for the neural networks with distributed delays and reaction-diffusion terms, based on constructing suitable Lyapunov functional, using M-matrix theory and some inequality techniques. Moreover, several remarks and the comparison with other results in early publication illuminate the advantages of the method. Finally, two numerical examples and the computational simulation are given to validate the theories.

关 键 词： 动态神经网络 分布参数 分布时滞 周期性

领　　域： [自动化与计算机技术] [自动化与计算机技术]