L∞ performance of single and interconnected neural networks with time-varying delay
L∞ performance of single and interconnected neural networks with time-varying delay
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DOI：
10.1016/j.ins.2016.02.004
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发表时间：
2016-06
期刊：
影响因子：
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通讯作者：
C. Ahn;P. Shi;R. Agarwal;Jing Xu
中科院分区：
文献类型：
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作者：
C. Ahn;P. Shi;R. Agarwal;Jing Xu
研究了时变时滞神经网络的L ∞性能分析问题。首先，基于Wirtinger型不等式和倒凸方法，给出了具有时变时滞和持续有界输入的单神经网络的L ∞性能的一个条件.然后，建立了保证变时滞互联神经网络L ∞性能的充分条件。数值算例表明了所得结果的有效性。
This paper is concerned with theL∞performance analysis problem for time-varying delayed neural networks. First, a condition is proposed for theL∞performance of single neural networks with time-varying delay and persistent bounded input based on the Wirtinger-type inequality together with the reciprocal convex approach. Then, sufficient conditions are established to ensure theL∞performance of interconnected neural networks with time-varying delay. Numerical examples are provided to show the effectiveness of the presented results.