期刊论文

Xu, Changjin

英文

Mathematics and Computers in Simulation

0378-4754

2021

182

471-494

10.1016/j.matcom.2020.11.023

This work is supported by National Natural Science Foundation of China (Nos. 61673008 and 62062018 ) and Project of High-level Innovative Talents of Guizhou Province, PR China ( [2016]5651 ) and Major Research Project of The Innovation Group of The Education Department of Guizhou Province, PR China ( [2017]039 ), Hunan Provincial Natural Science Foundation of China (No. 2020JJ4516 ), Key Project of Hunan Education Department, PR China ( 17A181 ), Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering ( Changsha University of Science & Technology, PR China ) ( 2018MMAEZD21 ), University Science and Technology Top Talents Project of Guizhou Province, PR China ( KY[2018]047 ), Foundation of Science and Technology of Guizhou Province, PR China ( [2019]1051 ), Guizhou University of Finance and Economics, PR China ( 2018XZD01 ). The authors would like to thank the referees and the editor for helpful suggestions incorporated into this paper.

本校为其他机构

The stability and Hopf bifurcation have important effect on the design of neural networks. By revealing the effect of parameters on the stability and Hopf bifurcation of neural networks, we can better apply neural networks to serve humanity. This article is principally concerned with the stability and the emergence of Hopf bifurcation of fractional-order BAM neural networks with multiple delays. Applying Laplace transform, stability theory and Hopf bifurcation knowledge of fractional-order differential systems, we establish a new sufficient condition to ensure the stability and the emergence o...