Global Uniform Asymptotic Fixed Deviation Stability and Stability for Delayed Fractional-order Memristive Neural Networks with Generic Memductance

被引：37

作者：

Chen, Jiejie ^{[1
,3
]}

Chen, Boshan ^{[2
]}

Zeng, Zhigang ^{[3
,4
]}

机构：

[1] Hubei Normal Univ, Coll Comp Sci & Technol, Huangshi 435002, Hubei, Peoples R China

[2] Hubei Normal Univ, Coll Math & Stat, Huangshi 435002, Hubei, Peoples R China

[3] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Hubei, Peoples R China

[4] Educ Minist China, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Hubei, Peoples R China

来源：

NEURAL NETWORKS | 2018年 / 98卷

关键词：

Memristive neural networks; Time-varying delays; Global uniform asymptotic stability; Fixed deviation stability; Discontinuous system; OUTPUT-FEEDBACK CONTROL; MARKOVIAN JUMP SYSTEMS; SYNCHRONIZATION; PERIODICITY;

D O I：

10.1016/j.neunet.2017.11.004

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, we study global uniform asymptotic fixed deviation stability and stability for a wide class of memristive neural networks with time-varying delays. Firstly, a new mathematical expression of the generic memductance (memristance) is proposed according to the feature of the memristor and the general current-voltage characteristic and a new class of neural networks is designed. Next, a new concept of stability (fixed deviation stability) is proposed in order to describe veritably the stability characteristics of the discontinuous system and the sufficient conditions are given to guarantee the global uniform asymptotic fixed deviation stability and stability of the new system. Finally, two numerical examples are provided to show the applicability and effectiveness of our main results. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：65 / 75

页数：11

共 50 条

[1] Asymptotic stability of delayed fractional-order neural networks with impulsive effects
Wang, Fei
Yang, Yongqing
Hu, Manfeng
[J]. NEUROCOMPUTING, 2015, 154 : 239 - 244
[2] Global Uniform Asymptotic Stability and Synchronization for Fractional-Order BAM Neural Networks with Time Delays
Pan, Qiujin
Chen, Boshan
[J]. 2017 4TH INTERNATIONAL CONFERENCE ON INFORMATION, CYBERNETICS AND COMPUTATIONAL SOCIAL SYSTEMS (ICCSS), 2017, : 464 - 469
[3] Asymptotic stability of delayed fractional-order fuzzy neural networks with impulse effects
Chen, Jiyang
Li, Chuandong
Yang, Xujun
[J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2018, 355 (15): : 7595 - 7608
[4] Asymptotic Stability of Fractional-Order Incommensurate Neural Networks
Chen, Liping
Gu, Panpan
Lopes, Antonio M.
Chai, Yi
Xu, Shuiqing
Ge, Suoliang
[J]. NEURAL PROCESSING LETTERS, 2023, 55 (05) : 5499 - 5513
[5] Asymptotic Stability of Fractional-Order Incommensurate Neural Networks
Liping Chen
Panpan Gu
António M. Lopes
Yi Chai
Shuiqing Xu
Suoliang Ge
[J]. Neural Processing Letters, 2023, 55 : 5499 - 5513
[6] Stability analysis of fractional-order delayed neural networks
Li, Ruoxia
Cao, Jinde
Alsaedi, Ahmad
Alsaadi, Fuad
[J]. NONLINEAR ANALYSIS-MODELLING AND CONTROL, 2017, 22 (04): : 505 - 520
[7] Stability and synchronization of fractional-order memristive neural networks with multiple delays
Chen, Liping
Cao, Jinde
Wu, Ranchao
Tenreiro Machado, J. A.
Lopes, Antonio M.
Yang, Hejun
[J]. NEURAL NETWORKS, 2017, 94 : 76 - 85
[8] Asymptotic stability and synchronization of fractional delayed memristive neural networks with algebraic constraints
Wu, Xiang
Liu, Shutang
Wang, Huiyu
[J]. COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2022, 114
[9] Global asymptotic stability of impulsive fractional-order BAM neural networks with time delay
Fei Wang
Yongqing Yang
Xianyun Xu
Li Li
[J]. Neural Computing and Applications, 2017, 28 : 345 - 352
[10] Global asymptotic stability of impulsive fractional-order BAM neural networks with time delay
Wang, Fei
Yang, Yongqing
Xu, Xianyun
Li, Li
[J]. NEURAL COMPUTING & APPLICATIONS, 2017, 28 (02): : 345 - 352

← 1 2 3 4 5 →