首页> 外文会议>Proceedings of the 17th Iranian Conference of Biomedical Engineering >Novel global exponential stability condition for discrete-time recurrent neural networks with random time-varying delays:
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Novel global exponential stability condition for discrete-time recurrent neural networks with random time-varying delays:

机译:具有随机时变时滞的离散时间递归神经网络的新型全局指数稳定性条件:

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摘要

In this paper, problem of stability for a class of discrete-time recurrent neural networks (DRNNs) with timevarying delay is considered. By employing the Lyapunov-Krasovskii function, a new condition for stability of time-delayed system is proposed. Result developed is in the term of linear matrix inequality (LMI) which can be easily checked by LMI Control toolbox. Furthermore, numerical examples are given to confirm the validity of the obtained approach.
机译:本文考虑一类具有时变时滞的离散时间递归神经网络(DRNN)的稳定性问题。利用Lyapunov-Krasovskii函数,为时滞系统的稳定性提出了新的条件。得出的结果是线性矩阵不等式(LMI),可以通过LMI Control工具箱轻松检查。此外,通过数值算例证实了所获得方法的有效性。

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