Fixed-time synchronization of coupled Cohen-Grossberg neural networks with and without parameter uncertainties

Fixed-time synchronization of coupled Cohen-Grossberg neural networks with and without parameter uncertainties
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具有和不具有参数不确定性的耦合 Cohen-Grossberg 神经网络的固定时间同步

DOI:
10.1016/j.neucom.2018.07.013
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发表时间:
2018-11
期刊:
影响因子:
6
通讯作者:
Zewei Zheng
Zewei Zheng
中科院分区:
计算机科学2区
文献类型:
--
作者:
Yanli Huang;Shuihan Qiu;Shunyan Ren;Zewei Zheng

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研究了具有常耦合和时滞耦合的耦合Cohen-Grossberg神经网络(CGNN)的定时同步问题。通过构造合适的Lyapunov泛函,得到了耦合CGNN实现定时同步的判据。此外,当参数不确定时,给出了保证耦合CGNN鲁棒定时同步的充分条件。类似地,还讨论了耦合的CGNN包含延迟耦合的情况。最后,给出了两个数值算例,验证了所得结果的有效性。
This paper is devoted to fixed-time synchronization for coupled Cohen–Grossberg neural networks (CGNNs) with constant coupling and delayed coupling. By constructing suitable Lyapunov functional, a criterion is obtained to guarantee that coupled CGNNs achieves fixed-time synchronization. Furthermore, when parameter uncertainties occur, a sufficient condition for ensuring robust fixed-time synchronization of coupled CGNNs is presented. Similarly, the case that coupled CGNNs including delayed coupling is also discussed. Finally, two numerical examples are provided to show the availability for the acquired results.
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