[1]周伟松,王兴武,吴东海,等.一类随机模糊细胞神经网络的输入对状态稳定性分析[J].四川师范大学学报(自然科学版),2019,(01):104.[doi:10.3969/j.issn.1001-8395.2019.01.016]
 ZHOU Weisong,WANG Xingwu,WU Donghai,et al.Input-to-state Stability of a Class of Stochastic Fuzzy Cellular Neural Networks[J].Journal of SichuanNormal University,2019,(01):104.[doi:10.3969/j.issn.1001-8395.2019.01.016]
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一类随机模糊细胞神经网络的输入对状态稳定性分析()
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《四川师范大学学报(自然科学版)》[ISSN:1001-8395/CN:51-1295/N]

卷:
期数:
2019年01期
页码:
104
栏目:
基础理论
出版日期:
2018-12-15

文章信息/Info

Title:
Input-to-state Stability of a Class of Stochastic Fuzzy Cellular Neural Networks
文章编号:
1001-8395(2019)01-0104-07
作者:
周伟松 王兴武 吴东海 曾 豪
重庆邮电大学 工业物联网与网络化控制重点实验室/复杂系统智能分析与决策重点实验室, 重庆 400065
Author(s):
ZHOU Weisong WANG Xingwu WU Donghai ZENG Hao
Key Laboratory of Industrial Internet of Things & Networked Control/Key Lab of Intelligent Analysis and Decision on Complex Systems, Chongqing University of Posts and Telecommunications, Chongqing 400065
关键词:
时滞 模糊 M矩阵 细胞神经网络 输入对状态稳定
Keywords:
delay fuzzy M matrix cellular neural networks input-to-state stability
分类号:
O110.87
DOI:
10.3969/j.issn.1001-8395.2019.01.016
文献标志码:
A
摘要:
研究一类带时变系数的随机泛函模糊细胞神经网络在均方意义下的指数输入对状态稳定性.利用Itô公式、Razumikhin技巧和建立Halanay微分不等式,得到该系统在均方意义下的指数输入对状态稳定性的2个充分条件.最后,给出一个数值仿真例子用以来说明得到的判据的正确性和有效性.
Abstract:
In this paper, we investigate the mean-square exponential input-to-state stability of a class of stochastic fuzzy cellular neural networks with time-varying coefficients. By using Ito formula, Razumikhin technique and constructing Halanay-type differential equalities, two sufficient conditions that guarantee the mean-square exponential input-to-state stability of our considered neural networks are obtained. Finally, we give a numerical example to illustrate the correctness and effectiveness of our results.

参考文献/References:

[1] CHUA L O, YANG L B. Cellular neural networks:theory and applications[J]. IEEE Trans Circuits Syst,1988,35:1257-1290.
[2] YANG T, YANG L B, WU C W, et al. Fuzzy cellular neural network:theory and applications[C]//Proc 4th IEEE Int Workshop Cell Neur Netw Their Appl,1996:181-186,225-230.
[3] YANG T, YANG L B. The global stability of fuzzy cellular neural network[J]. IEEE Trans Circ Syst-I:Fund Theor Appl,1996,43:880-883.
[4] YANG T, YANG L B. Fuzzy cellular neural network:a new paradigm for image processing[J]. Int J Circ Theor Appl,1997,25:469-481.
[5] HUANG T W. Exponential stability of delayed fuzzy cellular neural networks with diffusion[J]. Chaos Soliton Fractal,2007,31:658-664.
[6] WANG X H, XU D Y. Global exponential stability of impulsive fuzzy cellular neural networks with mixed delays and reaction-diffusion terms[J]. Chao Solit Fract,2009,42:2713-2721.
[7] LONG S J, SONG Q K, WANG X H, et al. Stability analysis of fuzzy cellular neural networks with time delay in the leakage term and impulsive perturbations[J]. J Franklin Inst,2012,349:2461-2479.
[8] YANG X S, YANG Z C. Synchronization of T-S fuzzy complex dynamical networks with time-varying impulsive delays and stochastic effects[J]. Fuzzy Sets and Systems,2014,235:25-43.
[9] LONG S J, XU D Y. Global exponential p-stability of stochastic non-autonomous Takagi-Sugeno fuzzy cellular neural networks with time-varying delays and impulses[J]. Fuzzy Sets and Systems,2014,253:82-100.
[10] WANG X H, LI S Y, XU D Y. Globally exponential stability of periodic solutions for impulsive neutral-type neural networks with delays[J]. Nonlinear Dynam,2011,64:65-75.
[11] HE D H, XU D Y. Attracting and invariant sets of fuzzy Cohen-Grossberg neural networks with time-varying delays[J]. Physics Letters,2008,A372:7057-7062.
[12] ZHU Q X, LI X D. Exponential and almost sure exponential stability of stochastic fuzzy delayed Cohen-Grossberg neural networks[J]. Fuzzy Sets and Systems,2012,203:74-94.
[13] ZHONG S M, LIU X Z. Exponential stability and periodicity of cellular neural networks with time delay[J]. Mathematical and Computer Modelling,2007,45:1231-1240.
[14] SONTAG E D. Smooth stabilition implies corprime factorization[J]. IEEE Trans Auto Control,1989,34:435-443.
[15] SONTAG E D. Further facts about input-to-state stabilization[J]. IEEE Trans Auto Control,1990,35:473-476.
[16] ZHOU W S, TENG L Y, XU D Y. Mean-square exponentially input-to-state stability of stochastic Cohen-Grossberg neural networks with time-varying delays[J]. Neurocomputing,2015,153:54-61.
[17] 周伟松,赵永红. 具时变时滞的随机模糊Cohen-Grossberg神经网络的均方指数输入状态稳定性[J]. 四川大学学报(自然科学版),2016,53(4):731-735.
[18] 徐道义. 泛函微分方程中的Razumikhin技巧[J]. 四川师范大学学报(自然科学报),1995,18(4):41-47.

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备注/Memo

备注/Memo:
收稿日期:2018-06-23 接受时间:2018-08-30
基金项目:重庆市教委一般科研项目(KJ1704099)
第一作者简介:周伟松(1988—),男,讲师,主要从事微分方程稳定性理论的研究,E-mail:zhouws@cqupt.edu.cn
更新日期/Last Update: 2018-12-15