Finite-time stability of fractional-order fuzzy cellular neural networks with time delays

被引：62
作者：
Du, Feifei [1 ,2 ,3 ]
Lu, Jun-Guo [1 ,2 ,3 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
[2] Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
[3] Shanghai Engn Res Ctr Intelligent Control & Manag, Shanghai 200240, Peoples R China
来源：
FUZZY SETS AND SYSTEMS | 2022年 / 438卷
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Finite-time stability; Fractional-order; Fuzzy cellular neural network; Gronwall inequality; Delay; DIFFERENTIAL-EQUATIONS; INTEGRAL-INEQUALITIES; GRONWALL INEQUALITY; GLOBAL STABILITY; SYSTEMS; CRITERIA; DESIGN; SYNCHRONIZATION; OSCILLATION; LEAKAGE;
D O I：
10.1016/j.fss.2021.08.011
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The finite-time stability of fractional-order fuzzy cellular neural networks with time delays is investigated. One of the difficulties in stability analysis of fractional-order delayed systems lies in how to handle the delay terms in the systems. In view of this difficulty, firstly, a new fractional-order Gronwall inequality with time delay is developed; this can be widely used to study finite time stability of a variety of fractional-order systems with time delays. Secondly, a new criterion for the finite-time stability of fractional-order fuzzy cellular neural networks with time delays is derived in terms of this inequality; it is less conservative than the one using the existing fractional-order Gronwall inequality with time delays. Finally, two examples are given to expound the effectiveness and less conservativeness of the proposed results.(c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码：107 / 120
页数：14
相关论文
共 60 条
[1]   Survey of Fuzzy Min-Max Neural Network for Pattern Classification Variants and Applications [J].
Al Sayaydeh, Osama Nayel ;
Mohammed, Mohammed Falah ;
Lim, Chee Peng .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2019, 27 (04) :635-645
[2]   Finite-time stability analysis of fractional-order memristive fuzzy cellular neural networks with time delay and leakage term [J].
Ali, M. Syed ;
Narayanan, G. ;
Saroha, Sumit ;
Priya, Bandana ;
Thakur, Ganesh Kumar .
MATHEMATICS AND COMPUTERS IN SIMULATION, 2021, 185 :468-485
[3]   Finite Time Stability Analysis of Fractional-Order Complex-Valued Memristive Neural Networks with Proportional Delays [J].
Ali, M. Syed ;
Narayanan, G. ;
Orman, Zeynep ;
Shekher, Vineet ;
Arik, Sabri .
NEURAL PROCESSING LETTERS, 2020, 51 (01) :407-426
[4]   Dynamic stability analysis of stochastic fractional-order memristor fuzzy BAM neural networks with delay and leakage terms [J].
Ali, M. Syed ;
Narayanan, Govindasamy ;
Shekher, Vineet ;
Alsulami, Hamed ;
Saeed, Tareq .
APPLIED MATHEMATICS AND COMPUTATION, 2020, 369
[5]   Global stability analysis of fractional-order fuzzy BAM neural networks with time delay and impulsive effects [J].
Ali, M. Syed ;
Narayanan, G. ;
Sevgen, Selcuk ;
Shekher, Vineet ;
Arik, Sabri .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2019, 78
[6]   Controller design for finite-time and fixed-time stabilization of fractional-order memristive complex-valued BAM neural networks with uncertain parameters and time-varying delays [J].
Arslan, Emel ;
Narayanan, G. ;
Ali, M. Syed ;
Arik, Sabri ;
Saroha, Sumit .
NEURAL NETWORKS, 2020, 130 :60-74
[7]   AN APPLICATION OF SMALL-WORLD CELLULAR NEURAL NETWORKS ON ODOR CLASSIFICATION [J].
Ayhan, Tuba ;
Yalcin, Mustak E. .
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 2012, 22 (01)
[8]   Stationary oscillation of interval fuzzy cellular neural networks with mixed delays under impulsive perturbations [J].
Balasubramaniam, P. ;
Kalpana, M. ;
Rakkiyappan, R. .
NEURAL COMPUTING & APPLICATIONS, 2013, 22 (7-8) :1645-1654
[9]   On the oscillation of fractional-order delay differential equations with constant coefficients [J].
Bolat, Yasar .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2014, 19 (11) :3988-3993
[10]   Design automation of cellular neural networks for data fusion applications [J].
Chatziagorakis, Prodromos ;
Sirakoulis, Georgics Ch ;
Lygouras, John N. .
MICROPROCESSORS AND MICROSYSTEMS, 2012, 36 (01) :33-44
123456