期刊论文

Xu, Changjin

英文

AIP Advances

2158-3226

2020

10

7

075022

10.1063/5.0012896

This work was supported by the National Natural Science Foundation of China (Grant No. 61673008), the Project of High-level Innovative Talents of Guizhou Province (Grant No. [2016]5651), the Major Research Project of The Innovation Group of The Education Department of Guizhou Province (Grant No. [2017]039), the Innovative Exploration Project of Guizhou University of Finance and Economics (Grant No. [2017]5736-015), the Project of Key Laboratory of Guizhou Province with Financial and Physical Features (Grant No. [2017]004), the Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering (Changsha University of Science and Technology) (Grant No. 2018MMAEZD21), the University Science and Technology Top Talents Project of Guizhou Province (Grant No. KY[2018]047), the Guizhou University of Finance and Economics (Grant No. 2018XZD01) and Key Project of Hunan Education Department (17A181). The authors would like to thank the referees and the editor for helpful suggestions incorporated into this paper. The authors declare that they have no competing interests.

本校为其他机构

In the present work, we mainly focus on shunting inhibitory cellular neural networks (SICNNs) involving leakage delays and proportional delays. By applying the inequality technique, a novel sufficient criterion to ascertain the convergence of every solution of SICNNs with leakage delays and proportional delays is derived. Simulation results are delineated to substantiate the correctness of our theoretical findings. Up to now, very few scholars deal with the neural networks with leakage delays and proportional delays. The derived concl...