Finite-Time Stabilization of Competitive Neural Networks With Time-Varying Delays
研究了具有离散时变时滞的竞争神经网络的有限时间镇定问题，通过设计不连续状态反馈控制器简化了现有结果，并给出了全局指数镇定的条件，最后用三个例子验证了理论的有效性。
This article investigates finite-time stabilization of competitive neural networks with discrete time-varying delays (DCNNs). By virtue of comparison strategies and inequality techniques, finite-time stabilization of the underlying DCNNs is analyzed by designing a discontinuous state feedback controller, which simplifies the controller design and proof processes of some existing results. Meanwhile, global exponential stabilization of the DCNNs is provided under a continuous state feedback controller. In addition, global exponential stability of the DCNNs is shown as an M-matrix, which contains some published outcomes as special cases. Finally, three examples are given to illuminate the validity of the theories.