Novel stability criteria for fuzzy Hopfield neural networks based on an improved homogeneous matrix polynomials technique
查看参考文献29篇
|
文摘
|
The global stability problem of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks (FHNNs) with time delays is investigated. Novel LMI-based stability criteria are obtained by using Lyapunov functional theory to guarantee the asymptotic stability of the FHNNs with less conservatism. Firstly, using both Finsler's lemma and an improved homogeneous matrix polynomial technique, and applying an affine parameter-dependent Lyapunov-Krasovskii functional, we obtain the convergent LMI-based stability criteria. Algebraic properties of the fuzzy membership functions in the unit simplex are considered in the process of stability analysis via the homogeneous matrix polynomials technique. Secondly, to further reduce the conservatism, a new right-hand-side slack variables introducing technique is also proposed in terms of LMIs, which is suitable to the homogeneous matrix polynomials setting. Finally, two illustrative examples are given to show the efficiency of the proposed approaches. |
|
来源
|
Chinese Physics. B
,2012,21(10):100701-1-100701-10 【核心库】
|
|
DOI
|
10.1088/1674-1056/21/10/100701
|
|
关键词
|
Hopfield neural networks
;
linear matrix inequality
;
Takagi-Sugeno fuzzy model
;
homogeneous polynomially technique
|
|
地址
|
1.
School of Mathematics, Jilin Normal University, Siping, 136000
2.
Institute of Systems Science, Northeastern University, Shenyang, 110004
|
|
语种
|
英文 |
|
ISSN
|
1674-1056 |
|
学科
|
非线性科学 |
|
基金
|
国家自然科学基金
;
the Natural Science Foundation of Jilin Province, China
|
|
文献收藏号
|
CSCD:4701580
|
参考文献 共
29
共2页
|
|
1.
Hopfied J J.
Proc. Natl. Acad. Sci. USA,1982,79:2554
|
被引
1
次
|
|
|
|
|
2.
Farrel J.
IEEE Trans. Circuits Syst,1990,37:877
|
被引
1
次
|
|
|
|
|
3.
Zhang W Y.
Chin. Phys. B,2011,20:030701
|
被引
5
次
|
|
|
|
|
4.
Zhang H G.
Chin. Phys. B,2009,18:3325
|
被引
6
次
|
|
|
|
|
5.
Wang Z D.
Phys. Lett. A,2006,354:288
|
被引
5
次
|
|
|
|
|
6.
Cui B T. New results on global exponential stability of competitive neural networks with different time scales and time-varying delays.
Chin. Phys. B,2008,17:1670
|
被引
9
次
|
|
|
|
|
7.
Ji Y. Improved delay-dependent globally asymptotic stability of delayed uncertain recurrent neural networks with Markovian jumping parameters.
Chin. Phys. B,2010,19:060512
|
被引
2
次
|
|
|
|
|
8.
Li D. Exponential stability of cellular neural networks with multiple time delays and impulsive effects.
Chin. Phys. B,2008,17:4091
|
被引
13
次
|
|
|
|
|
9.
Lee S M. A new approach to stability analysis of neural networks withtime-varying delay via novelLyapunov--Krasovskii functional.
Chin. Phys. B,2010,19:050507
|
被引
7
次
|
|
|
|
|
10.
Kwon O M. New results on stability criteria for neural networks with time-varying delays.
Chin. Phys. B,2011,20:050505
|
被引
11
次
|
|
|
|
|
11.
Lakshmanan S. Linear matrix inequality approach for robust stability analysis for stochastic neural networks with time-varying delay.
Chin. Phys. B,2011,20:040204
|
被引
8
次
|
|
|
|
|
12.
Takagi T.
IEEE Trans. Syst. Man, Cybernt,1985,15:116
|
被引
805
次
|
|
|
|
|
13.
Wang L X.
IEEE Trans. Neural Networks,1992,3:807
|
被引
192
次
|
|
|
|
|
14.
Gong D W. Novel stability and stabilization criteria for Takagi-Sugeno fuzzy time-delay systems.
Chin. Phys. B,2012,21:030204
|
被引
7
次
|
|
|
|
|
15.
Zhang H G.
IEEE Trans. Fuzzy Syst,2011,19:478
|
被引
6
次
|
|
|
|
|
16.
Feng Y F.
Chin. Phys. B,2010,19:120502
|
被引
1
次
|
|
|
|
|
17.
Zhang H G.
IEEE Trans. Syst. Man, Cybernt. B,2011,41:1313
|
被引
5
次
|
|
|
|
|
18.
Huang H.
IEEE Trans. Circ. Syst. II: Exp. Briefs,2005,52:251
|
被引
8
次
|
|
|
|
|
19.
Lou X Y.
Fuzzy Sets and Systems,2007,158:2746
|
被引
5
次
|
|
|
|
|
20.
Ali M S.
Commun. Nonlinear Sci. Numer. Simul,2009,14:2776
|
被引
1
次
|
|
|
|
|
了解气象卫星更多信息，请访问