School of Mathematics, Southeast University, Nanjing 210096, China.
School of Mathematics, Southeast University, Nanjing 210096, China; NAAM Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Neural Netw. 2018 Feb;98:122-153. doi: 10.1016/j.neunet.2017.11.001. Epub 2017 Nov 23.
This paper investigates the stability and lag synchronization for memristor-based fuzzy Cohen-Grossberg bidirectional associative memory (BAM) neural networks with mixed delays (asynchronous time delays and continuously distributed delays) and impulses. By applying the inequality analysis technique, homeomorphism theory and some suitable Lyapunov-Krasovskii functionals, some new sufficient conditions for the uniqueness and global exponential stability of equilibrium point are established. Furthermore, we obtain several sufficient criteria concerning globally exponential lag synchronization for the proposed system based on the framework of Filippov solution, differential inclusion theory and control theory. In addition, some examples with numerical simulations are given to illustrate the feasibility and validity of obtained results.
本文研究了具有混合时滞(异步时滞和连续分布时滞)和脉冲的基于忆阻器的模糊 Cohen-Grossberg 双向联想记忆(BAM)神经网络的稳定性和滞后同步。通过应用不等式分析技术、同胚理论和一些合适的 Lyapunov-Krasovskii 泛函,建立了平衡点唯一性和全局指数稳定性的一些新的充分条件。此外,我们基于 Filippov 解、微分包含理论和控制理论的框架,得到了关于所提出系统全局指数滞后同步的几个充分准则。此外,还给出了一些数值模拟示例,以验证所得结果的可行性和有效性。