Wu Ligang, Feng Zhiguang, Zheng Wei Xing
Space Control and Inertial Technology Research Center, Harbin Institute of Technology, China.
IEEE Trans Neural Netw. 2010 Sep;21(9):1396-407. doi: 10.1109/TNN.2010.2056383. Epub 2010 Aug 19.
This paper is concerned with the problem of exponential stability analysis of continuous-time switched delayed neural networks. By using the average dwell time approach together with the piecewise Lyapunov function technique and by combining a novel Lyapunov-Krasovskii functional, which benefits from the delay partitioning method, with the free-weighting matrix technique, sufficient conditions are proposed to guarantee the exponential stability for the switched neural networks with constant and time-varying delays, respectively. Moreover, the decay estimates are explicitly given. The results reported in this paper not only depend upon the delay but also depend upon the partitioning, which aims at reducing the conservatism. Numerical examples are presented to demonstrate the usefulness of the derived theoretical results.
本文关注连续时间切换时滞神经网络的指数稳定性分析问题。通过使用平均驻留时间方法结合分段Lyapunov函数技术，并将一种受益于延迟分区方法的新型Lyapunov-Krasovskii泛函与自由加权矩阵技术相结合，分别提出了充分条件以保证具有常数时滞和时变时滞的切换神经网络的指数稳定性。此外，还明确给出了衰减估计。本文所报道的结果不仅依赖于时滞，还依赖于分区，其目的在于降低保守性。给出了数值例子以证明所推导理论结果的有效性。
