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具有区间时变时滞的递归神经网络的新的时滞相关稳定性判据。

New delay dependent stability criteria for recurrent neural networks with interval time-varying delay.

机构信息

School of Mathematics and Computer Science, Mianyang Normal University, Mianyang, Sichuan 621000, PR China.

School of Marxism, Mianyang Normal University, Mianyang, Sichuan 621000, PR China.

出版信息

ISA Trans. 2014 Jul;53(4):994-9. doi: 10.1016/j.isatra.2014.05.009. Epub 2014 Jun 5.

DOI:10.1016/j.isatra.2014.05.009
PMID:24908560
Abstract

This paper is concerned with the delay dependent stability criteria for a class of static recurrent neural networks with interval time-varying delay. By choosing an appropriate Lyapunov-Krasovskii functional and employing a delay partitioning method, the less conservative condition is obtained. Furthermore, the LMIs-based condition depend on the lower and upper bounds of time delay. Finally, a numerical example is also designated to verify the reduced conservatism of developed criteria.

摘要

本文研究了一类具有区间时变时滞的静态递归神经网络的时滞相关稳定性判据。通过选择合适的 Lyapunov-Krasovskii 泛函并采用时滞分区方法，得到了更保守的条件。此外，基于 LMI 的条件取决于时滞的下限和上限。最后，还设计了一个数值例子来验证所提出判据的保守性降低。

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