时变时滞Cohen-Grossberg神经网络的全局鲁棒指数稳定性

2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI:10.1109/ICACI.2012.6463285

Xiaolin Li, Jia Jia

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引用次数: 0

摘要

研究了Cohen-Grossberg神经网络的全局鲁棒指数稳定性问题。利用新的不等式和线性矩阵不等式技术，导出了保证平衡点全局鲁棒指数稳定的新的充分条件。最后通过数值算例验证了理论结果的有效性。

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Global robust exponential stability for Cohen-Grossberg neural networks with time-varying delays

Global robust exponential stability problems for Cohen-Grossberg neural networks are investigated in this paper. New sufficient conditions are derived to ensure the global robust exponential stability of the equilibrium point by using a new inequality and linear matrix inequality technique. A numerical example is given to show the effectiveness of the theoretical results.

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2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)

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