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Comparative exploration on bifurcation behavior for integer-order and fractional-order delayed BAM neural networks

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成果类型:
期刊论文
作者:
Xu, Changjin;Mu, Dan;Liu, Zixin;Pang, Yicheng;Liao, Maoxin;...
作者机构:
[Xu, Changjin] Guizhou Univ Finance & Econ, Guizhou Key Lab Econ Syst Simulat, Guiyang 550025, Peoples R China.
[Mu, Dan; Liu, Zixin; Pang, Yicheng] Guizhou Univ Finance & Econ, Sch Math & Stat, Guiyang 550004, Peoples R China.
[Liao, Maoxin] Univ South China, Sch Math & Phys, Hengyang 421001, Peoples R China.
[Li, Peiluan] Henan Univ Sci & Technol, Sch Math & Stat, Luoyang 471023, Peoples R China.
[Yao, Lingyun] Guizhou Univ Finance & Econ, Lib, Guiyang 550004, Peoples R China.
语种:
英文
关键词:
fractional-order BAM neural networks;integer-order delayed BAM neural networks;Hopf bifurcation;stability;bifurcation diagram
期刊:
Nonlinear Analysis-Modelling and Control
ISSN:
1392-5113
年:
2022
卷:
27
期:
1
页码:
1030-1053
基金类别:
National Natural Science Foundation of China [61673008, 62062018]; Guizhou Key Laboratory of Big Data Statistical Analysis [[2019]5103]; Project of High-Level Innovative Talents of Guizhou Province [[2016]5651]; Basic Research Program of Guizhou Province [ZK[2022]025]; Natural Science Project of the Education Department of Guizhou Province [KY[2021]031]; Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering (Changsha University of Science Technology) [2018MMAEZD21]; University Science and Technology Top Talents Project of Guizhou Province [KY[2018]047]; Foundation of Science and Technology of Guizhou Province [[2019]1051]; Guizhou University of Finance and Economics [2018XZD01, 2017SWBZD09]; Joint Fund Project of Guizhou University of Finance and Economics and Institute of International Trade and Economic Cooperation of Ministry of Commerce on Contiguous areas of extreme poverty Poor peasant psychological Poverty alleviation [2017SWBZD09]
机构署名:
本校为其他机构
院系归属:
数理学院
摘要:
In the present study, we deal with the stability and the onset of Hopf bifurcation of two type delayed BAM neural networks (integer-order case and fractional-order case). By virtue of the characteristic equation of the integer-order delayed BAM neural networks and regarding time delay as critical parameter, a novel delay-independent condition ensuring the stability and the onset of Hopf bifurcation for the involved integer-order delayed BAM neural networks is built. Taking advantage of Laplace transform, stability theory and Hopf bifurcation knowledge of fractional-order differential equations...

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