Mittag-Leffler stability of fractional-order neural networks in the presence of generalized piecewise constant arguments

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• 作者：Ailong Wu^a ; ^b ; ^c ; ^d ; ^{hbnuwu@yeah.net} ; Ling Liu^a ; ^{lliu9308@sina.com} ; Tingwen Huang^b ; ^{tingwen.huang@qatar.tamu.edu} ; Zhigang Zeng^c ; ^{hustzgzeng@gmail.com}
• 关键词：Fractional-order systems ; Generalized piecewise constant arguments ; Neurodynamic systems ; Mittag-Leffler stability
• 刊名：Neural Networks
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：85
• 期：Complete
• 页码：118-127
• 全文大小：857 K
• 卷排序：85

文摘

Neurodynamic system is an emerging research field. To understand the essential motivational representations of neural activity, neurodynamics is an important question in cognitive system research. This paper is to investigate Mittag-Leffler stability of a class of fractional-order neural networks in the presence of generalized piecewise constant arguments. To identify neural types of computational principles in mathematical and computational analysis, the existence and uniqueness of the solution of neurodynamic system is the first prerequisite. We prove that the existence and uniqueness of the solution of the network holds when some conditions are satisfied. In addition, self-active neurodynamic system demands stable internal dynamical states (equilibria). The main emphasis will be then on several sufficient conditions to guarantee a unique equilibrium point. Furthermore, to provide deeper explanations of neurodynamic process, Mittag-Leffler stability is studied in detail. The established results are based on the theories of fractional differential equation and differential equation with generalized piecewise constant arguments. The derived criteria improve and extend the existing related results.