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Robust Stability in Interval Delayed Neural Networks of Neutral Type

机译:间隔时滞神经网络的鲁棒稳定性。

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摘要

In this paper, the problem of global robust stability (GRAS) is investigated for a class of interval neural networks described by nonlinear delayed differential equations of the neutral type. A sufficient criterion is derived by an approach combining the Lyapunov-Krasovskii functional with the linear matrix inequality (LMI). Finally, the effectiveness of the present results is demonstrated by a numerical example.
机译:在本文中,针对一类由中立型非线性时滞微分方程描述的区间神经网络,研究了全局鲁棒稳定性(GRAS)问题。通过将Lyapunov-Krasovskii泛函与线性矩阵不等式(LMI)相结合的方法可以得出充分的判据。最后,通过数值例子证明了本结果的有效性。

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