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LMI-based criterion for global asymptotic stability of BAM neural networks with time delays

机译:具有时滞的基于LMI的BAM神经网络的全局渐近稳定性准则

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摘要

This paper presents a stability criterion for global asymptotic stability of the equilibrium point for Bidirectional Associative Memory (BAM) neural networks with fixed time delays. An approach combining the Lyapunov-Krasovskii functional with Linear Matrix Inequality (LMI) is taken to investigate the stability of the system. A delay-dependent LMI criterion is derived. Finally, a numerical example is given to illustrate the results.
机译:本文提出了具有固定时滞的双向联想记忆(BAM)神经网络平衡点的全局渐近稳定性的稳定性判据。采取了将Lyapunov-Krasovskii泛函与线性矩阵不等式(LMI)相结合的方法来研究系统的稳定性。推导了依赖于延迟的LMI标准。最后,给出一个数值例子来说明结果。

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