首页> 外文会议>International Conference on Inventive Computation Technologies >Improved stability analysis of delayed neural networks via Wirtinger-based double integral inequality
【24h】

Improved stability analysis of delayed neural networks via Wirtinger-based double integral inequality

机译:通过基于Wirtinger的双积分不等式改进延迟神经网络的稳定性分析

获取原文

摘要

This paper is concerned with the stability analysis of neural networks with time-varying delays using reciprocally convex combination approach and Wirtinger-based double integral inequality. The time-varying delay is need to be bounded and continuous. By constructing suitable Lyapunov-Krasovskii functional (LKF) and introducing appropriate terms in dealing with the positiveness of the LKF, we establish new stability and stabilization criteria in terms of linear matrix inequalities (LMIs). The present method leads to some significant improvements over existing results. A numerical example is given to illustrate the usefulness and effectiveness of the proposed theoretical results.
机译:本文研究了基于时变时滞的神经网络的稳定性分析,采用的是双向凸组合法和基于Wirtinger的双积分不等式。时变延迟需要是有界且连续的。通过构造合适的Lyapunov-Krasovskii泛函(LKF)并引入适当的术语来处理LKF的正性,我们根据线性矩阵不等式(LMI)建立了新的稳定性和稳定标准。本方法导致对现有结果的一些重大改进。数值例子说明了所提出的理论结果的实用性和有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号