Dissipativity and stability analysis of fractional-order complex-valued neural networks with time delay

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• 作者：G. Velmurugan^a ; R. Rakkiyappan^a ; ^{rakkigru@gmail.com} ; V. Vembarasan^b ; Jinde Cao^c ; ^d ; ^{jdcao@seu.edu.cn} ; Ahmed Alsaedi^e
• 关键词：Fractional-order ; Complex-Valued Neural Networks (CVNNs) ; Dissipativity ; Asymptotic stability ; Fractional Halanay inequality ; Time delay
• 刊名：Neural Networks
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：86
• 期：Complete
• 页码：42-53
• 全文大小：662 K
• 卷排序：86

文摘

As we know, the notion of dissipativity is an important dynamical property of neural networks. Thus, the analysis of dissipativity of neural networks with time delay is becoming more and more important in the research field. In this paper, the authors establish a class of fractional-order complex-valued neural networks (FCVNNs) with time delay, and intensively study the problem of dissipativity, as well as global asymptotic stability of the considered FCVNNs with time delay. Based on the fractional Halanay inequality and suitable Lyapunov functions, some new sufficient conditions are obtained that guarantee the dissipativity of FCVNNs with time delay. Moreover, some sufficient conditions are derived in order to ensure the global asymptotic stability of the addressed FCVNNs with time delay. Finally, two numerical simulations are posed to ensure that the attention of our main results are valuable.