标题:
具有时变传输时滞的高阶Cohen-Grossberg型BAM神经网络的周期解Periodic Solution for a Class of Higher-Order Cohen-Grossberg-Type BAM Neural Networks with Periodic Coefficients and Time-Varying Delays
作者:
田晓红, 徐瑞
关键字:
时变传输时滞, 周期系数, 周期解, 全局稳定Time-Varying Delays, Periodic Coefficients, Periodic Solution, Global Stability
期刊名称:
《Advances in Applied Mathematics》, Vol.5 No.4, 2016-11-30
摘要:
本文研究了具有周期系数和时变传输时滞的高阶Cohen-Grossberg型BAM神经网络，利用拓扑度中的Mawhin延拓定理，讨论了系统周期解的存在性，并通过构造适当的Lyapunov泛函，给出了周期解全局稳定的充分条件。
A class of higher-order Cohen-Grossberg-type BAM neural networks with periodic coefficients and time-varying delays is studied in this paper. By using the continuation theorem of Mawhin’s coincidence degree theory, the existence of periodic solutions of networks is discussed, and by constructing appropriate Lyapunov functional, sufficient conditions are established for the global stability of the periodic solution.