Equilibria and Stability Analysis of Cohen-Grossberg BAM Neural Networks on Time Scale  

作　　者：LIU Mingshuo FANG Yong DONG Huanhe 

机构地区：[1]College of Mathematics and Systems Science,Shandong University of Science and Technology,Qingdao,266590,China

出　　处：《Journal of Systems Science & Complexity》2022年第4期1348-1373,共26页系统科学与复杂性学报（英文版）

基　　金：supported by the National Natural Science Foundation of China under Grant Nos.12105161,11975143;the Natural Science Foundation of Shandong Province under Grant No.ZR2019QD018。

摘　　要：This paper considers the Cohen-Grossberg BAM neural networks(CG-BAMNNs) on time scale, which can unify and generalize the continuous and discrete systems. First, the criteria for the existence and uniqueness of the equilibrium of CG-BAMNNs are derived on time scale. Then based on that, the authors give the criteria for the stability and estimation of equilibrium of the CG-BAMNNs on time scale. The method proposed in this paper unifies and generalizes the continuous and discrete CGBAMNNs systems, and is applicable to some other neural network systems on time scale with practical meaning. The effectiveness of the proposed criteria for delayed CG-BAMNNs is demonstrated by numerical simulation.

关 键 词：Cohen-Grossberg BAM neural networks EXISTENCE numerical simulation stability UNIQUENESS 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]