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

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-09-05 DOI:10.1002/mma.10434
Chengdai Huang, Lei Fu, Shuang Liu, Jinde Cao, Mahmoud Abdel‐Aty, Heng Liu
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Abstract

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.
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涉及中性项的延迟分数阶神经网络的动态分岔
在克拉默法则的帮助下,很好地探讨了具有中性延迟的分数阶神经网络的稳定性和分岔问题。首先构建了三神经元中性型分数阶神经网络(NTFONN)。其次,使用卡普托分数阶导数的拉普拉斯变换。然后,利用特征方程解析法和克拉默法则,得到霍普夫分岔的存在性。此外,研究还表明,中性延迟在 NTFONN 中保持网络稳定和控制霍普夫分岔的发生方面起着非常重要的作用。研究进一步发现,与相应的整数阶 NTFONN 相比,所设计的 NTFONN 具有出色的稳定性能。最后,通过数值模拟证实了所获结果的可行性和有效性。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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