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Complete stability of cellular neural networks with unbounded time-varying delays

机译:具有无限时变延迟的细胞神经网络的完全稳定性

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In this paper, we are concerned with the delayed cellular neural networks (DCNNs) in the case that the time-varying delays are unbounded. Under some conditions, it shows that the DCNNs can exhibit 3" equilibrium points. Then, we track the dynamics of u(r)(r > 0) in two cases with respect to different types of subset regions in which u(0) is located. It concludes that every solution trajectory u(t) would converge to one of the equilibrium points despite the time-varying delays, that is, the delayed cellular neural networks are completely stable. The method is novel and the results obtained extend the existing ones. In addition, two illustrative examples are presented to verify the effectiveness of our results.
机译:在本文中,我们关注时变延迟不受限制的情况下的时延细胞神经网络(DCNN)。在某些情况下,它表明DCNNs可以显示3“平衡点。然后,针对两种类型的u(0)是子集区域,我们跟踪u(r)(r> 0)在两种情况下的动力学结论是,尽管存在时变时滞,但每条解轨迹u(t)都将收敛到一个平衡点,即时滞细胞神经网络是完全稳定的,该方法新颖,所得结果扩展了现有方法的位置。此外,还提供了两个说明性示例来验证我们的结果的有效性。

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