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State estimation for neural networks of neutral-type with interval time-varying delays

机译:具有间隔时变时滞的中立型神经网络的状态估计

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摘要

In this paper, the design problem of state estimator for a class of neural networks of neutral-type with interval time-varying delays is studied. The interval time-varying delay does not have constraint that its derivative is less than 1. The constraint is widely used to deal with time-varying delays in many papers. A delay-dependent linear matrix inequality (LMI) criterion for existence of the estimator is proposed by using Lyapunov method. The criterion can be easily solved by various convex optimization algorithms. A numerical example is given to show the effectiveness of proposed method. (C) 2008 Elsevier Inc. All rights reserved.
机译:本文研究了一类具有间隔时变时滞的中立型神经网络的状态估计器的设计问题。间隔时变延迟不具有其导数小于1的约束。在许多论文中,该约束被广泛用于处理时变延迟。利用Lyapunov方法,提出了估计器存在的依赖于时延的线性矩阵不等式(LMI)准则。该准则可以通过各种凸优化算法轻松解决。数值算例表明了该方法的有效性。 (C)2008 Elsevier Inc.保留所有权利。

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