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首页> 外文期刊>International Journal of Information Acquisition >STABILITY CRITERION OF A CLASS OF NEUTRAL NEURAL NETWORK WITH UNCERTAINTIES AND TIME-VARYING DELAY
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STABILITY CRITERION OF A CLASS OF NEUTRAL NEURAL NETWORK WITH UNCERTAINTIES AND TIME-VARYING DELAY

机译:一类具有不确定性和时变时延的神经网络的稳定性判据

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摘要

Under reasonable postulated conditions of time-varying delay, the stability of a class of neutral neural network is probed. Based on the proper construction of the Lyapunov functional, a new method of predicating the uniformly asymptotic stability of this kind of neutral network is presented. The criterion is based on the positive definite solutions of a Riccati equation and a discrete Lyapunov equation, and is converted to LMI problem. The validity of the criterion is also confirmed by the simulation.
机译:在合理的时变时滞假设条件下,研究了一类中立神经网络的稳定性。在适当构造Lyapunov泛函的基础上,提出了一种预测这种中立网络的一致渐近稳定性的新方法。该准则基于Riccati方程和离散Lyapunov方程的正定解,并转换为LMI问题。模拟也证实了准则的有效性。

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