...
首页> 外文期刊>Computational intelligence and neuroscience >New Results on Passivity Analysis of Stochastic Neural Networks with Time-Varying Delay and Leakage Delay
【24h】

New Results on Passivity Analysis of Stochastic Neural Networks with Time-Varying Delay and Leakage Delay

机译:随机性神经网络与时变延迟泄漏延迟的新结果

获取原文
获取原文并翻译 | 示例

摘要

The passivity problem for a class of stochastic neural networks systems (SNNs) with varying delay and leakage delay has been further studied in this paper. By constructing a more effective Lyapunov functional, employing the free-weighting matrix approach, and combining with integral inequality technic and stochastic analysis theory, the delay-dependent conditions have been proposed such that SNNs are asymptotically stable with guaranteed performance. The time-varying delay is divided into several subintervals and two adjustable parameters are introduced; more information about time delay is utilised and less conservative results have been obtained. Examples are provided to illustrate the less conservatism of the proposed method and simulations are given to show the impact of leakage delay on stability of SNNs.
机译:本文进一步研究了具有变化延迟和泄漏延迟的一类随机神经网络系统(SNNS)的被动问题。 通过构建更有效的Lyapunov功能,采用自由加权矩阵方法,并结合整体不等式技术和随机分析理论,已经提出了延迟依赖性条件,使得SNNS具有保证性能的渐近稳定性。 将时变延迟分为几个子内部,介绍了两个可调参数; 利用有关时间延迟的更多信息,并获得了更少的保守结果。 提供了示例以说明所提出的方法的保守性较少,并给出了泄漏延迟对SNNS稳定性的影响。

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