Dynamical bifurcations in a delayed fractional-order neural network involving neutral terms

被引：0

作者：

Huang, Chengdai ^{[1
]}

Fu, Lei ^{[1
]}

Liu, Shuang ^{[1
]}

Cao, Jinde ^{[2
]}

Abdel-Aty, Mahmoud ^{[3
,4
]}

Liu, Heng ^{[5
]}

机构：

[1] Xinyang Normal Univ, Sch Math & Stat, Xinyang, Peoples R China

[2] Southeast Univ, Sch Math, Nanjing, Peoples R China

[3] Jadara Univ, Jadara Res Ctr, Irbid, Jordan

[4] Ahlia Univ, Deanship Grad Studies & Res, Manama, Bahrain

[5] Guangxi Minzu Univ, Sch Math & Phys, Nanning, Peoples R China

来源：

MATHEMATICAL METHODS IN THE APPLIED SCIENCES | 2025年 / 48卷 / 02期

基金：

中国国家自然科学基金;

关键词：

fractional order; Hopf bifurcation; neural networks; neutral delay; stability; HOPF-BIFURCATION; STABILITY ANALYSIS; MULTIPLE DELAYS; MODEL;

D O I：

10.1002/mma.10434

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The stability and bifurcations of a fractional-order neural network with a neutral delay are nicely contemplated with the help of the Cramer's rule. The three-neuron neutral-type fractional-order neural network (NTFONN) is firstly constructed. Secondly, the Laplace transform of the Caputo fractional-order derivatives is used. Afterward, using the analytical method of characteristic equations and Cramer's rule, the existence of Hopf bifurcations is obtained. Moreover, it indicates that the neutral delay plays an enormously significant role in remaining network stabilization and controlling the occurrence of Hopf bifurcations in NTFONN. It further detects that the devised NTFONN has outstanding stability performance in comparison with the corresponding integer-order one. Finally, numerical simulations are developed to confirm the feasibility and validity of the obtained results.

引用

页码：2253 / 2266

页数：14

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