Synchronization of Discrete-Time Fractional-Order Complex-Valued Neural Networks with Distributed Delays

被引：1

作者：

Perumal, R. ^{[1
]}

Hymavathi, M. ^{[2
]}

Ali, M. Syed ^{[2
]}

Mahmoud, Batul A. A. ^{[3
]}

Osman, Waleed M. ^{[4
]}

Ibrahim, Tarek F. ^{[5
]}

机构：

[1] SRM Inst Sci & Technol, Fac Engn & Technol, Dept Math, Kattankulathur 603203, Tamil Nadu, India

[2] Thiruvalluvar Univ, Dept Math, Complex Syst & Networked Sci Res Lab, Vellore 632115, Tamil Nadu, India

[3] King Khalid Univ, Fac Sci & Arts Sarat Abeda, Dept Math, Abha 62521, Saudi Arabia

[4] King Khalid Univ, Fac Sci & Arts, Dept Math, Abha 62529, Saudi Arabia

[5] King Khalid Univ, Fac Sci & Arts Mahayel, Dept Math, Abha 62529, Saudi Arabia

来源：

FRACTAL AND FRACTIONAL | 2023年 / 7卷 / 06期

关键词：

fractional order; synchronization; complex-valued; discrete-time; neural networks; GLOBAL EXPONENTIAL STABILITY; DYNAMICAL NETWORKS; VARYING DELAYS; ROBUST SYNCHRONIZATION; SYSTEMS;

D O I：

10.3390/fractalfract7060452

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This research investigates the synchronization of distributed delayed discrete-time fractional-order complex-valued neural networks. The necessary conditions have been established for the stability of the proposed networks using the theory of discrete fractional calculus, the discrete Laplace transform, and the theory of fractional-order discrete Mittag-Leffler functions. In order to guarantee the global asymptotic stability, adequate criteria are determined using Lyapunov's direct technique, the Lyapunov approach, and some novel analysis techniques of fractional calculation. Thus, some sufficient conditions are obtained to guarantee the global stability. The validity of the theoretical results are finally shown using numerical examples.

引用

页数：20

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