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New delay-interval-dependent stability criteria for switched Hopfield neural networks of neutral type with successive time-varying delay components

机译:具有连续时变时滞分量的中立型切换Hopfield神经网络的新的依赖于时间间隔的稳定性准则

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摘要

This paper deals with the problem of delay-interval-dependent stability criteria for switched Hopfield neural networks of neutral type with successive time-varying delay components. A novel Lyapunov–Krasovskii (L–K) functionals with triple integral terms which involves more information on the state vectors of the neural networks and upper bound of the successive time-varying delays is constructed. By using the famous Jensen’s inequality, Wirtinger double integral inequality, introducing of some zero equations and using the reciprocal convex combination technique and Finsler’s lemma, a novel delay-interval dependent stability criterion is derived in terms of linear matrix inequalities, which can be efficiently solved via standard numerical software. Moreover, it is also assumed that the lower bound of the successive leakage and discrete time-varying delays is not restricted to be zero. In addition, the obtained condition shows potential advantages over the existing ones since no useful term is ignored throughout the estimate of upper bound of the derivative of L–K functional. Using several examples, it is shown that the proposed stabilization theorem is asymptotically stable. Finally, illustrative examples are presented to demonstrate the effectiveness and usefulness of the proposed approach with a four-tank benchmark real-world problem.
机译:本文研究具有连续时变时滞的中立型交换Hopfield神经网络的时滞相关稳定性准则。构造了具有三重积分项的新颖Lyapunov-Krasovskii(L-K)泛函,其中涉及神经网络的状态向量以及连续时变时滞的上限的更多信息。利用著名的詹森不等式,维特林格双积分不等式,引入一些零方程,以及采用倒凸组合技术和芬斯勒引理,根据线性矩阵不等式推导了一种新的时滞依赖稳定准则,可以有效地解决该问题。通过标准数值软件。此外,还假定连续泄漏和离散时变延迟的下限不限于零。此外,获得的条件显示出优于现有条件的潜在优势,因为在整个L-K函数导数上限的估计中没有忽略任何有用的术语。使用几个例子,表明所提出的稳定定理是渐近稳定的。最后,给出了说明性示例,以证明所提出的方法具有四罐基准实际问题的有效性和实用性。

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