Linguistic flow in fuzzy discrete-time cellular neural networks and its stability

被引：3
作者：
Yang, T [1 ]
Yang, LB
Yang, CL
Yang, XP
Yang, HN
机构：
[1] Univ Calif Berkeley, Elect Res Lab, Berkeley, CA 94720 USA
[2] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA
[3] Univ EZhou, Ezhou 436000, Hubei, Peoples R China
[4] China Construct Bank, Songjiang Subbranch, Shanghai 201611, Peoples R China
[5] Hua Zhong Agr Univ, Dept Fishery, Wuhan 430070, Peoples R China
[6] Wuhan Univ, Sch Law, Wuhan 430070, Peoples R China
来源：
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS | 1998年 / 45卷 / 09期
关键词：
D O I：
10.1109/81.721252
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A type-III fuzzy discrete-time cellular neural network (FDTCNN) structure is presented to implement local linguistic dynamic systems. The theoretical results of equilibrium points and stability of this FDTCNN are presented. The state transient process of this FDTCNN is analyzed by using fuzzy mathematics, Markov chain, and graph theory. An efficient algorithm is presented to check the existence of globally stable equilibrium point. Examples in a two-cell FDTCNN are used to demonstrate theoretical results. Finally, designing examples of a 1-D FDTCNN are presented to simulate the traffic flow of a highway system. Computer simulation results are given.
引用
收藏
页码：869 / 878
页数：10
相关论文
共 50 条
[21]   On discrete-time cellular neural networks for associative memories [J].
Grassi, G .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS, 2001, 48 (01) :107-111
[22]   ON THE CONVERGENCE OF RECIPROCAL DISCRETE-TIME CELLULAR NEURAL NETWORKS [J].
PERFETTI, R .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS, 1993, 40 (04) :286-287
[23]   Existence and stability analysis of discrete-time fuzzy BAM neural networks with delays and impulses [J].
Wang, Chao ;
Li, Yongkun .
International Journal of Computational and Mathematical Sciences, 2012, 6 (01) :47-56
[24]   Exponential stability of discrete-time hopfield neural networks [J].
Guo, SJ ;
Huang, LH ;
Wang, L .
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2004, 47 (8-9) :1249-1256
[25]   Stability of discrete-time hopfield neural networks with delays [J].
Zhang, Qiang .
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2007, 14 :105-107
[26]   Stability analysis of discrete-time recurrent neural networks [J].
Barabanov, NE ;
Prokhorov, DV .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (02) :292-303
[27]   Global stability of stochastic, discrete-time neural networks [J].
Joy, MP .
Proceedings of the Ninth IASTED International Conference on Artificial Intelligence and Soft Computing, 2005, :130-134
[28]   MEMRISTOR CELLULAR AUTOMATA AND MEMRISTOR DISCRETE-TIME CELLULAR NEURAL NETWORKS [J].
Itoh, Makoto ;
Chua, Leon O. .
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 2009, 19 (11) :3605-3656
[29]   Stability and bifurcation of a class of discrete-time neural networks [J].
He, Wangli ;
Cao, Jinde .
APPLIED MATHEMATICAL MODELLING, 2007, 31 (10) :2111-2122
[30]   Chaos and asymptotical stability in discrete-time neural networks [J].
Chen, LN ;
Aihara, K .
PHYSICA D-NONLINEAR PHENOMENA, 1997, 104 (3-4) :286-325
12345