首页> 外文期刊>International journal of computer mathematics >Novel delay-dependent stability condition for mixed delayed stochastic neural networks with leakage delay signals
【24h】

Novel delay-dependent stability condition for mixed delayed stochastic neural networks with leakage delay signals

机译:具有泄漏时滞信号的混合时滞随机神经网络的时滞相关稳定性新条件

获取原文
获取原文并翻译 | 示例
           

摘要

In this paper, the problem of stability condition for mixed delayed stochastic neural networks with neutral delay and leakage delay is investigated. A novel Lyapunov functional is constructed with double and triple integral terms. New sufficient conditions are derived to guarantee the global asymptotic stability of the concerned neural network. This paper is more general than the paper by Zhu et al. [Robust stability of Markovian jump stochastic neural networks with time delays in the leakage terms, Neural Process. Lett. 41 (2015), pp. 1-27]. In our paper, we considered both the neutral delay and leakage delay, but the paper by Zhu et al. is not considering the neutral delay. Also we employed triple integrals in the Lyapunov functional which is not used in the paper by Zhu et al. Finally, two numerical examples are provided to show the effectiveness of the theoretical results.
机译:研究了具有中性时滞和泄漏时滞的混合时滞随机神经网络的稳定性条件问题。具有双重和三重积分项的新颖Lyapunov泛函构造。得出了新的充分条件,以保证相关神经网络的全局渐近稳定性。本文比Zhu等人的论文更具笼统性。 [具有渗漏项时滞的Markovian跳跃随机神经网络的鲁棒稳定性,神经过程。来吧41(2015),第1-27页]。在我们的论文中,我们同时考虑了中性延迟和泄漏延迟,但朱等人的论文却没有考虑到。没有考虑中立的延迟。同样,我们在Lyapunov函数中采用了三重积分,这在Zhu等人的论文中没有使用。最后,提供了两个数值例子来说明理论结果的有效性。

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