当前位置: X-MOL 学术Circuits Syst. Signal Process. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Finite-time Synchronization of Fuzzy Cellular Neural Networks with Stochastic Perturbations and Mixed Delays
Circuits, Systems, and Signal Processing ( IF 1.8 ) Pub Date : 2021-01-02 , DOI: 10.1007/s00034-020-01631-3
Dongsheng Xu , Ting Wang , Ming Liu

This paper investigates finite-time synchronization for fuzzy cellular neural networks (FCNNs). In contrast to correlative studies, discrete time delays, distributed delays and stochastic perturbations are taken into consideration. A mathematical model of this kind of FCNN is considered for the first time. By employing the Lyapunov method, graph theory, the feedback control technique and stochastic finite-time synchronization theory, several sufficient conditions for finite-time synchronization of FCNNs are derived. The upper bound of the stochastic settling time is explicitly proposed and has a close relationship with the topological structure of the neural network. Finally, a numerical example is used to validate the practicability and feasibility of the theoretical results we propose.

中文翻译:

具有随机扰动和混合延迟的模糊细胞神经网络的有限时间同步

本文研究了模糊细胞神经网络 (FCNN) 的有限时间同步。与相关研究相比,离散时间延迟、分布式延迟和随机扰动都被考虑在内。这种FCNN的数学模型是第一次考虑。利用Lyapunov方法、图论、反馈控制技术和随机有限时间同步理论,推导出FCNNs有限时间同步的几个充分条件。随机稳定时间的上界被明确提出,与神经网络的拓扑结构有密切关系。最后,通过一个数值例子来验证我们提出的理论结果的实用性和可行性。
更新日期:2021-01-02
down
wechat
bug