具有不确定性和无界分布延迟的随机中立神经网络的全局鲁棒准则

2011 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems Pub Date : 2011-03-20 DOI:10.1109/CYBER.2011.6011808

Guoquan Liu, Simon X. Yang

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引用次数: 0

摘要

研究了一类具有不确定性和无界分布延迟的随机中立型神经网络的全局鲁棒稳定性分析问题。利用Lyapunov-Krasovskii泛函方法和自由加权矩阵技术，得到了新的线性矩阵不等式稳定性判据。最后，通过两个算例验证了所得条件的有效性。

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Global robust criteria for stochastic neutral neural networks with uncertainties and unbounded distributed delay

The problem of global robust stability analysis is studied for a class of stochastic neutral neural networks with uncertainties and unbounded distributed delay. Novel stability criteria are obtained in terms of linear matrix inequality (LMI) by employing the Lyapunov-Krasovskii functional method and using the free-weighting matrices technique. In addition, two examples are given to show the effectiveness of the obtained conditions.

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来源期刊

2011 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

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