Fixed-time synchronization of proportional delay memristive complex-valued competitive neural networks

被引：0
作者：
Han, Jiapeng
Zhou, Liqun [1 ]
机构：
[1] Tianjin Normal Univ, Sch Math Sci, Tianjin 300387, Peoples R China
来源：
NEURAL NETWORKS | 2025年 / 188卷
关键词：
Fixed-time synchronization; Competitive neural networks; Proportional delays; Complex-valued neural networks; EXPONENTIAL SYNCHRONIZATION; STABILITY;
D O I：
10.1016/j.neunet.2025.107411
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The fixed-time synchronization (FXS) is considered for memristive complex-valued competitive neural networks (MCVCNNs) with proportional delays. Two less conservative criteria supporting the FXS of MCVCNNs are founded by involving Lyapunov method and inequality techniques. Suitable switch controllers are designed by defining different norms of complex numbers instead of treating complex-valued neural networks as two real-valued systems. Furthermore, the settling time (ST) has been approximated. Finally, two simulations are shown to confirm the effectiveness of criteria in this paper and the outcomes of practical application in image protection.
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页数：10
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