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Exponential convergence and stability of delayed fuzzy cellular neural networks with time-varying coefficients 被引量：1

Exponential convergence and stability of delayed fuzzy cellular neural networks with time-varying coefficients
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摘要 In this paper, the dynamic behaviors of fuzzy cellular neural networks （FCNNs） with time-varying coefficients and delays are considered. Some criteria are established to ensure the exponential convergence or exponential stability of such neural networks. The effectiveness of obtained results is illustrated by a numerical example. In this paper, the dynamic behaviors of fuzzy cellular neural networks （FCNNs） with time-varying coefficients and delays are considered. Some criteria are established to ensure the exponential convergence or exponential stability of such neural networks. The effectiveness of obtained results is illustrated by a numerical example.
作者 Manchun TAN
机构地区 Department of Mathematics
出处 《控制理论与应用（英文版）》 EI 2011年第4期500-504,共5页
基金 supported by the National Natural Science Foundation of China (No. 50578064) the Foundation of Science and Technology of Guangdong Province in China (No. 2009B011400046)
关键词 Delayed neural networks Exponential convergence Exponential stability Fuzzy cellular neural networks Time-varying coefficients Delayed neural networks Exponential convergence Exponential stability Fuzzy cellular neural networks Time-varying coefficients
分类号 TP18 [自动化与计算机技术—控制理论与控制工程] TP183 [自动化与计算机技术—控制理论与控制工程]
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参考文献17

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  • 3M. Tan, Y. Zhang. New sufficient conditions for global asymptotic stability of Cohen-Grossberg neural networks with time-varying delays. Nonlinear Analysis: Real World Applications, 2009, 10(4): 2139 - 2145.
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控制理论与应用（英文版）
2011年 第4期

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