Finite-time synchronization for fuzzy inertial cellular neural networks with time-varying delays via integral inequality

被引：2

作者：

Wang, Zhenjie ^{[1
]}

Cui, Wenxia ^{[1
]}

Jin, Wenbin ^{[1
]}

机构：

[1] Shanghai Univ Engn Sci, Sch Math Phys & Stat, Shanghai 201620, Peoples R China

来源：

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2021年 / 41卷 / 02期

关键词：

Finite-time synchronization; complex networks; time-varying delays; integral inequality; GLOBAL EXPONENTIAL STABILITY; ALMOST-PERIODIC SOLUTIONS; ASYMPTOTIC STABILITY; EXISTENCE;

D O I：

10.3233/JIFS-211065

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper mainly considers the finite-time synchronization problem of fuzzy inertial cellular neural networks (FICNNs) with time-varying delays. By constructing the suitable Lyapunov functional, and using integral inequality techniques, several sufficient criteria have been proposed to ensure the finite-time synchronization for the addressed (FICNNs). Without applying the known finite-time stability theorem, which is widely used to solve the finite-time synchronization problems for (FICNNs). In this paper, the proposed method is relatively convenient to solve finite-time synchronization problem of the addressed system, this paper extends the research works on the finite-time synchronization of (FICNNs). Finally, numerical simulations illustrated verify the effectiveness of the proposed results.

引用

页码：3653 / 3666

页数：14

共 35 条

[11] Global Asymptotic Stabilization of Cellular Neural Networks with Proportional Delay via Impulsive Control [J].

Guan, Kaizhong ;

Yang, Junhao .

NEURAL PROCESSING LETTERS, 2019, 50 (02) :1969-1992

[12] Global exponential stability of neural networks with time-varying delay based on free-matrix-based integral inequality [J].

He, Yong ;

Ji, Meng-Di ;

Zhang, Chuan-Ke ;

Wu, Min .

NEURAL NETWORKS, 2016, 77 :80-86

[13] New Results on Periodicity of Non-autonomous Inertial Neural Networks Involving Non-reduced Order Method [J].

Huang, Chuangxia ;

Yang, Luanshan ;

Liu, Bingwen .

NEURAL PROCESSING LETTERS, 2019, 50 (01) :595-606

[14] Exponential stability of inertial neural networks involving proportional delays and non-reduced order method [J].

Huang, Chuangxia .

JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, 2020, 32 (01) :133-146

[15] New studies on dynamic analysis of inertial neural networks involving non-reduced order method [J].

Huang, Chuangxia ;

Liu, Bingwen .

NEUROCOMPUTING, 2019, 325 :283-287

[16] Finite-time synchronization of inertial memristive neural networks with time-varying delays via sampled-date control [J].

Huang, Dasong ;

Jiang, Minghui ;

Jian, Jigui .

NEUROCOMPUTING, 2017, 266 :527-539

[17] Finite-time stability of a class of fuzzy cellular neural networks with multi-proportional delays [J].

Jia, Renwei .

FUZZY SETS AND SYSTEMS, 2017, 319 :70-80

[18] Finite-time synchronization for fuzzy neutral-type inertial neural networks with time-varying coefficients and proportional delays [J].

Jian, Jigui ;

Duan, Liyan .

FUZZY SETS AND SYSTEMS, 2020, 381 :51-67

[19] Existence and global exponential stability of anti-periodic solutions for delayed quaternion-valued cellular neural networks with impulsive effects [J].

Li, Yongkun ;

Qin, Jiali ;

Li, Bing .

MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2019, 42 (01) :5-23

[20] Global exponential stability for quaternion-valued recurrent neural networks with time-varying delays [J].

Liu, Yang ;

Zhang, Dandan ;

Lu, Jianquan .

NONLINEAR DYNAMICS, 2017, 87 (01) :553-565

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