Global Mittag-Leffler stabilization of fractional-order bidirectional associative memory neural networks

被引：86
作者：
Wu, Ailong [1 ,2 ,3 ]
Zeng, Zhigang [1 ,2 ]
Song, Xingguo [4 ]
机构：
[1] Hubei Normal Univ, Coll Math & Stat, Huangshi 435002, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Peoples R China
[3] Xi An Jiao Tong Univ, Inst Informat & Syst Sci, Xian 710049, Peoples R China
[4] Southwest Jiaotong Univ, Sch Mech Engn, Chengdu 610031, Peoples R China
来源：
NEUROCOMPUTING | 2016年 / 177卷
关键词：
Fractional-order systems; Bidirectional associative memory neural networks; Mittag-Leffler stability; TIME-VARYING DELAYS; EXPONENTIAL STABILITY; ROBUST STABILITY; LEAKAGE DELAYS; ANTIPERIODIC SOLUTIONS; ASYMPTOTIC STABILITY; IMPULSIVE CONTROL; STATE ESTIMATION; CONTROL-SYSTEMS; SYNCHRONIZATION;
D O I：
10.1016/j.neucom.2015.11.055
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, stabilization control of fractional-order bidirectional associative memory neural networks is formulated and studied. By estimating Mittag-Leffler function and some novel analysis techniques of fractional calculation, a generalized Gronwall-like inequality of Caputo fractional derivative is established. Then by applying Lyapunov approach, linear state feedback control law and partial state feedback control law are presented to stabilize the fractional-order bidirectional associative memory neural networks. This analysis framework can be applied to closed-loop control of fractional-order systems. A numerical example is given to show the effectiveness of the derived results via computer simulations. Crown Copyright (C) 2015 Published by Elsevier B.V. All rights reserved.
引用
收藏
页码：489 / 496
页数：8
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