基于量化控制的耦合神经网络渐近二部同步

Ting Liu, Junhong Zhao, Peng Liu, Jian Yong, Shulong Fan, Junwei Sun
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引用次数: 0

摘要

研究了时变时滞耦合神经网络的二部同步问题。通过引入有效的量化控制器,实现了时变时滞耦合神经网络的二部同步,并利用Halanay不等式导出了保证二部同步的充分条件。此外,作为一种特例,在推论中还考虑了通过量化控制器实现无延迟耦合神经网络的二部同步。最后,通过数值算例验证了理论结果的正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Asymptotic Bipartite Synchronization of Coupled Neural Networks Via Quantized Control
This paper addresses the bipartite synchronization of coupled neural networks with time-varying delay. By introducing an effective quantized controller, the bipartite synchronization of coupled neural networks with time-varying delay is realized and sufficient conditions for assuring the bipartite synchronization are derived in virtue of a Halanay inequality. Moreover, the bipartite synchronization of coupled neural networks without delay via quantized controller is also taken into account in corollary as a special case. In the end, a numerical example is provided to demonstrate the correctness of theoretical results.
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