Robust stability analysis of Takagi-Sugeno uncertain stochastic fuzzy recurrent neural networks with mixed time-varying delays

被引：0

作者：

M.Syed Ali ^{[1
]}

机构：

[1] Department of Mathematics,Thiruvalluvar University,Vellore-632 106,Tamilnadu,India

来源：

Chinese Physics B | 2011年 / 20卷 / 08期

关键词：

recurrent neural networks; linear matrix inequality; Lyapunov stability; time-varying delays; TS fuzzy model;

D O I：

暂无

中图分类号：

O211.6 [随机过程]; TP183 [人工神经网络与计算];

学科分类号：

020208 ; 070103 ; 0714 ; 081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper,the global stability of Takagi-Sugeno (TS) uncertain stochastic fuzzy recurrent neural networks with discrete and distributed time-varying delays (TSUSFRNNs) is considered.A novel LMI-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of TSUSFRNNs.The proposed stability conditions are demonstrated through numerical examples.Furthermore,the supplementary requirement that the time derivative of time-varying delays must be smaller than one is removed.Comparison results are demonstrated to show that the proposed method is more able to guarantee the widest stability region than the other methods available in the existing literature.

引用

页码：5 / 19

页数：15

共 50 条

[1] Robust stability analysis of Takagi-Sugeno uncertain stochastic fuzzy recurrent neural networks with mixed time-varying delays
Ali, M. Syed
[J]. CHINESE PHYSICS B, 2011, 20 (08)
[2] Stability analysis of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays
Hou, Yi-You
Liao, Teh-Lu
Yan, Jun-Juh
[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2007, 37 (03): : 720 - 726
[3] A DELAY-DEPENDENT APPROACH TO ROBUST PASSIVITY ANALYSIS FOR TAKAGI-SUGENO FUZZY UNCERTAIN RECURRENT NEURAL NETWORKS WITH MIXED INTERVAL TIME-VARYING DELAYS
Tseng, K. H.
Tsai, J. S. H.
Lu, C. Y.
[J]. INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS, 2013, 21 (03) : 415 - 433
[4] A DELAY-DEPENDENT APPROACH TO ROBUST TAKAGI-SUGENO FUZZY CONTROL OF UNCERTAIN RECURRENT NEURAL NETWORKS WITH MIXED INTERVAL TIME-VARYING DELAYS
Tseng, K. H.
Tsai, J. S. H.
Lu, C. Y.
[J]. JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS, 2011, 20 (08) : 1571 - 1589
[5] Improved robust exponential stability for Takagi-Sugeno fuzzy uncertain systems with time-varying delays
Liu, Pin-Lin
[J]. JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS, 2016, 39 (02) : 150 - 158
[6] Improved Results on State Estimation for Uncertain Takagi-Sugeno Fuzzy Stochastic Neural Networks with Time-Varying Delays
Li, Yajun
Deng, Feiqi
Li, Jingzhao
[J]. INTERNATIONAL JOURNAL OF NONLINEAR SCIENCES AND NUMERICAL SIMULATION, 2017, 18 (06) : 495 - 505
[7] Stability Criteria for Stochastic Takagi-Sugeno Fuzzy Cohen-Grossberg BAM Neural Networks with Mixed Time-Varying Delays
Ali, Muhammed Syed
Balasubramaniam, Pagavathigounder
Rihan, Fathalla A.
Lakshmanan, Shanmugam
[J]. COMPLEXITY, 2016, 21 (05) : 143 - 154
[8] Robust passivity analysis for Takagi-Sugeno fuzzy stochastic Cohen-Grossberg interval neural networks with time-varying delays
Nagamani, G.
Balasubramaniam, P.
[J]. PHYSICA SCRIPTA, 2011, 83 (01)
[9] Stability analysis of Takagi-Sugeno stochastic fuzzy Hopfield neural networks with discrete and distributed time varying delays
Balasubramaniam, P.
Ali, M. Syed
[J]. NEUROCOMPUTING, 2011, 74 (10) : 1520 - 1526
[10] Passivity and passification for stochastic Takagi-Sugeno fuzzy systems with mixed time-varying delays
Song, Qiankun
Zhao, Zhenjiang
Yang, Jianxi
[J]. NEUROCOMPUTING, 2013, 122 : 330 - 337

← 1 2 3 4 5 →