Extended dissipative analysis for memristive neural networks with two additive time-varying delay components
Extended dissipative analysis for memristive neural networks with two additive time-varying delay components
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DOI：
10.1016/j.neucom.2016.07.054
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发表时间：
2016-12
期刊：
影响因子：
6
通讯作者：
Hongzhi Wei;Ruoxia Li;Chunrong Chen;Zhengwen Tu
中科院分区：
文献类型：
--
作者：
Hongzhi Wei;Ruoxia Li;Chunrong Chen;Zhengwen Tu
本文研究具有两个加性时变时滞的记忆神经网络的扩展耗散性。在给出记忆模型的基础上，利用Lyapunov泛函、积分不等式以及时变时滞之间的关系，建立了关于二次稳定性和扩展耗散性判据的一些基本结果。新的扩展耗散不等式包含多个加权矩阵，通过将加权矩阵转换为新的性能指标，扩展的耗散性将分别退化为H∞性能、L 2−L∞性能、无源性和耗散性。最后，给出了一个实例，证明了理论方法的显著改进。
This paper concentrates on the extended dissipativity of memristive neural networks with two additive time-varying delays. After giving a foundation to the memristive model, the paper establishes some fundamental results on quadratically stability and extended dissipativity criteria by means of the Lyapunov functional, integral inequality, as well as the relationship between time-varying delays. The novel extended dissipative inequality contains several weighting matrices, by converting the weighting matrices in a new performance index, the extended dissipativity will be degraded to the H∞ performance, L 2− L∞ performance, passivity and dissipativity, respectively. Finally, one example is given to substantiate the significant improvement of the theoretical approaches.