时滞惯性神经网络镇定的脉冲控制方法

Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India Pub Date : 2021-01-01 DOI:10.4108/eai.7-12-2021.2315115

K. R

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引用次数: 1

摘要

研究了基于脉冲量的时滞惯性神经网络的镇定问题。利用Lyapunov稳定性理论得到了稳定结果的时滞相关充分条件，该理论涉及Lyapunov- krasovskii泛函的构造。为了得到这些结果，考虑了时滞信息。在这里，时滞被认为是时变的，激活函数被假定为扇区有界的。推导的条件可以通过MATLAB进行验证。最后，给出了一个算例来支持推导结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Impulsive Control Approach to Stabilization of Delayed Inertial Neural Networks

: Stabilization of delayed inertial neural networks based on impulsesl is investigated in this paper. Delay-dependent sufficient conditions of stabilization results are obtained as linear matrix inequalities via Lyapunov stability theory which involves the construction of Lyapunov-Krasovskii functional. Information of time-delay is taken into account to obtain these results. Here, time-delay is considered to be time-varying and the activation function is assumed to be sector bounded. Derived conditions can be validated via MATLAB. Finally, an example is provided to support the derived results.

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Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India

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