Global exponential asymptotic stability of RNNs with mixed asynchronous time-varying delays

被引：2
作者：
Jia, Songfang [1 ]
Chen, Yanheng [1 ]
机构：
[1] Chongqing Three Gorges Univ, Dept Math, Wanzhou, Peoples R China
来源：
ADVANCES IN DIFFERENCE EQUATIONS | 2020年 / 2020卷 / 01期
关键词：
Recurrent neural networks; Equilibrium point; Exponential stability; Mixed asynchronous time-varying delay; RECURRENT NEURAL-NETWORKS; DISCRETE; SYNCHRONIZATION; SYSTEMS; DESIGN;
D O I：
10.1186/s13662-020-02648-3
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The present article addresses the exponential stability of recurrent neural networks (RNNs) with distributive and discrete asynchronous time-varying delays. Some novel algebraic conditions are obtained to ensure that for the model there exists a unique balance point, and it is global exponential asymptotically stable. Meanwhile, it also reveals the difference about the equilibrium point between systems with and without distributed asynchronous delay. One numerical example and its Matlab software simulations are given to illustrate the correctness of the present results.
引用
收藏
页数：14
相关论文
共 26 条
[1]   Analysis and design of associative memories based on recurrent neural network with discontinuous activation functions [J].
Bao, Gang ;
Zeng, Zhigang .
NEUROCOMPUTING, 2012, 77 (01) :101-107
[2]   Forecasting wind speed with recurrent neural networks [J].
Cao, Qing ;
Ewing, Bradley T. ;
Thompson, Mark A. .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2012, 221 (01) :148-154
[3]   Forecast of solar irradiance using recurrent neural networks combined with wavelet analysis [J].
Cao, SH ;
Cao, JC .
APPLIED THERMAL ENGINEERING, 2005, 25 (2-3) :161-172
[4]   Synchronization of memristive neural networks with mixed delays via quantized intermittent control [J].
Feng, Yuming ;
Yang, Xinsong ;
Song, Qiang ;
Cao, Jinde .
APPLIED MATHEMATICS AND COMPUTATION, 2018, 339 :874-887
[5]   Exponential synchronization of inertial neural networks with mixed delays via quantized pinning control [J].
Feng, Yuming ;
Xiong, Xiaolin ;
Tang, Rongqiang ;
Yang, Xinsong .
NEUROCOMPUTING, 2018, 310 :165-171
[6]   Hierarchical singleton-type recurrent neural fuzzy networks for noisy speech recognition [J].
Juang, Chia-Feng ;
Chiou, Chyi-Tian ;
Lai, Chun-Lung .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2007, 18 (03) :833-843
[7]   Isolated word recognition using modular recurrent neural networks [J].
Lee, T ;
Ching, PC ;
Chan, LW .
PATTERN RECOGNITION, 1998, 31 (06) :751-760
[8]   Discrete Analogue for a Class of Impulsive Cohen-Grossberg Neural Networks with Asynchronous Time-Varying Delays [J].
Li, Liangliang ;
Li, Chuandong .
NEURAL PROCESSING LETTERS, 2019, 49 (01) :331-345
[9]   Exponential stability of recurrent neural networks with time-varying discrete and distributed delays [J].
Li, Tao ;
Luo, Qi ;
Sun, Changyin ;
Zhang, Baoyong .
NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS, 2009, 10 (04) :2581-2589
[10]   Persistence of delayed cooperative models: Impulsive control method [J].
Li, Xiaodi ;
Yang, Xueyan ;
Huang, Tingwen .
APPLIED MATHEMATICS AND COMPUTATION, 2019, 342 (130-146) :130-146
123