Aperiodically intermittent quantized control-based exponential synchronization of quaternion-valued inertial neural networks

被引:0
|
作者
Fei, Jingnan [1 ]
Ren, Sijie [1 ]
Zheng, Caicai [1 ]
Yu, Juan [1 ,2 ]
Hu, Cheng [1 ,2 ]
机构
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830017, Peoples R China
[2] Xinjiang Key Lab Appl Math XJDX1401, Urumqi 830017, Peoples R China
基金
中国国家自然科学基金;
关键词
Quaternion-valued neural network; Exponential synchronization; Aperiodically intermittent quantized control; Inertial model; NON-REDUCED ORDER; STABILITY; DELAYS;
D O I
10.1016/j.neunet.2024.106669
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Inertial neural networks are proposed via introducing an inertia term into the Hopfield models, which make their dynamic behavior more complex compared to the traditional first-order models. Besides, the aperiodically intermittent quantized control over conventional feedback control has its potential advantages on reducing communication blocking and saving control cost. Based on these facts, we are mainly devoted to exploring of exponential synchronization of quaternion-valued inertial neural networks under aperiodically intermittent quantized control. Firstly, a compact quaternion-valued aperiodically intermittent quantized control protocol is developed, which can mitigate significantly the complexity of theoretical derivation. Subsequently, several concise criteria involving matrix inequalities are formulated through constructing a type of Lyapunov functional and employing a direct analysis approach. The correctness of the obtained results eventually is verified by a typical example.
引用
收藏
页数:10
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