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Bifurcation Analysis for Simplified Five-Neuron Bidirectional Associative Memory Neural Networks with Four Delays

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成果类型:
期刊论文
作者:
Xu, Changjin*;Liao, Maoxin;Li, Peiluan;Guo, Ying
通讯作者:
Xu, Changjin
作者机构:
[Xu, Changjin] Guizhou Univ Finance & Econ, Guizhou Key Lab Econ Syst Simulat, Guiyang 550004, Guizhou, 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.
[Guo, Ying] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China.
通讯机构:
[Xu, Changjin] G
Guizhou Univ Finance & Econ, Guizhou Key Lab Econ Syst Simulat, Guiyang 550004, Guizhou, Peoples R China.
语种:
英文
关键词:
BAM neural networks;Stability;Hopf bifurcation;Time delay
期刊:
Neural Processing Letters
ISSN:
1370-4621
年:
2019
卷:
50
期:
3
页码:
2219-2245
基金类别:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China [61673008]; Project of High-level Innovative Talents of Guizhou Province [[2016]5651]; Major Research Project of The Innovation Group of The Education Department of Guizhou Province [[2017]039]; Project of Key Laboratory of Guizhou Province with Financial and Physical Features [[2017]004]; Foundation of Science and Technology of Guizhou Province [[2018]1025, [2018]1020]
机构署名:
本校为其他机构
院系归属:
数理学院
摘要:
The paper deals with the stability and bifurcation analysis of a class of simplified five-neuron bidirectional associative memory neural networks with four delays. By discussing the characteristic transcendental equation and applying Hopf bifurcation theory, some sufficient conditions which guarantee the local stability and the existence of Hopf bifurcation of the neural networks are established. With the aid of the normal form theory and center manifold theory, we obtain some specific formulae to determine the stability and the direction of the Hopf bifurcation. Computer simulations are imple...

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