Global exponential stability of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays. (September 2016) - Song, Qiankun; Yan, Huan; Zhao, Zhenjiang; Liu, Yurong
Abstract: This paper investigates the stability problem for a class of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays. By employing the idea of vector Lyapunov function, M-matrix theory and inequality technique, several sufficient conditions are obtained to ensure the global exponential stability of equilibrium point. When the impulsive effects are not considered, several sufficient conditions are also given to guarantee the existence, uniqueness and global exponential stability of equilibrium point. Two examples are given to illustrate the effectiveness and lower level of conservatism of the proposed criteria in comparison with some existing results.