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Robust Stability of Inertial BAM Neural Networks with Time Delays and Uncertainties via Impulsive Effect

机译:具有时滞和不确定性的惯性BAM神经网络的鲁棒稳定性

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This paper investigates the robust stability of inertial bidirectional association memory (BAM) neural networks with time delays and uncertainties via impulsive control. Firstly, utilizing suitable variable substitution, the seconded-order inertial BAM neural networks can be transformed into first-order differential equations. Secondly, Under the framework of Lyapunov stability method, Halanay inequality and impulsive differential inequations, we develop some techniques of impulsive to achieve the robust stability of inertial BAM neural networks. These obtained criteria are capable of reducing computational burden in the theoretical part. Some effective sufficient conditions are established for the realization of stability of the underlying network. Finally, an illustrative example is given to verify the validity of the obtained results.
机译:本文通过脉冲控制研究了具有时滞和不确定性的惯性双向联想记忆(BAM)神经网络的鲁棒稳定性。首先,利用适当的变量替换,可以将二阶惯性BAM神经网络转换为一阶微分方程。其次,在Lyapunov稳定性方法,Halanay不等式和脉冲微分不等式的框架下,我们开发了一些脉冲技术来实现惯性BAM神经网络的鲁棒稳定性。这些获得的标准能够减轻理论部分的计算负担。为实现底层网络的稳定性建立了一些有效的充分条件。最后,给出了一个示例性例子来验证所获得结果的有效性。

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