Lagrange stability of complex-valued neural networks with time-varying delays

Zhengwen Tu, Jinde Cao
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Abstract

In this paper, the Lagrange stability of complex-valued neural networks(CVNNs) with time-varying delays is considered. By employing matrix measure approach and generalized Halanay inequality, several sufficient criteria are derived to ascertain the global Lagrange stability for the addressed neural networks. Meanwhile, the globally exponentially attractive sets are exhibited. Finally, two numerical examples are presented to verify our theoretical results.
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时变时滞复值神经网络的拉格朗日稳定性
研究了时变时滞复值神经网络的拉格朗日稳定性问题。利用矩阵测度方法和广义Halanay不等式,导出了确定神经网络全局拉格朗日稳定性的几个充分准则。同时,给出了全局指数吸引集。最后,给出了两个数值算例来验证我们的理论结果。
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