A novel direct method to H∞ synchronization of switching inertial neural networks with mixed time-varying delays

被引：4

作者：

Zhang, Xian ^{[1
,2
]}

Yuan, Shilei ^{[1
]}

Wang, Yantao ^{[1
,2
]}

Yang, Xiaona ^{[1
,2
]}

机构：

[1] Heilongjiang Univ, Sch Math Sci, Harbin 150080, Peoples R China

[2] Heilongjiang Univ, Heilongjiang Prov Key Lab Theory & Computat Compl, Harbin 150080, Peoples R China

来源：

NEUROCOMPUTING | 2024年 / 598卷

关键词：

Switching inertial neural networks; Mixed time-varying delays; Parameterized system solution-based direct; analysis method; FINITE-TIME; LAG SYNCHRONIZATION; STABILIZATION; STABILITY;

D O I：

10.1016/j.neucom.2024.128039

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, the H Po synchronization problem of switching inertial neural networks with mixed time-varying delays is discussed. A parameterized system solution-based direct analysis method combined with minimum residence time method is proposed to solve the considered problem. The advantage of this method is that no model transformation or construction of Lyapunov-Krasovskii functional is required, thus reducing the complexity of derivation process. In addition, the resulting synchronization conditions composed of some simple scalar inequalities can be easily solved via MATLAB. Finally, the reliability of the theoretical results is illustrated by numerical simulations.

引用

页数：11

共 44 条

[1] Finite-time and fixed-time synchronization of a class of inertial neural networks with multi-proportional delays and its application to secure communication [J].

Alimi, Adel M. ;

Aouiti, Chaouki ;

Assali, El Abed .

NEUROCOMPUTING, 2019, 332 :29-43

[2] The Optimization of Control Parameters: Finite-time and Fixed-time Synchronization of Inertial Memristive Neural Networks with Proportional Delays and Switching Jumps Mismatch [J].

Chang, Qi ;

Yang, Yongqing ;

Li, Li ;

Wang, Fei .

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2021, 19 (07) :2491-2499

[3] Global exponential synchronization of discrete-time high-order switched neural networks and its application to multi-channel audio encryption [J].

Dong, Zeyu ;

Wang, Xin ;

Zhang, Xian ;

Hu, Mengjie ;

Dinh, Thach Ngoc .

NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2023, 47

[4] A nonsingular M-matrix-based global exponential stability analysis of higher-order delayed discrete-time Cohen-Grossberg neural networks [J].

Dong, Zeyu ;

Wang, Xin ;

Zhang, Xian .

APPLIED MATHEMATICS AND COMPUTATION, 2020, 385

[5] Study of Adversarial Machine Learning with Infrared Examples for Surveillance Applications [J].

Edwards, DeMarcus ;

Rawat, Danda B. .

ELECTRONICS, 2020, 9 (08) :1-13

[6] Passivity-based synchronization for Markov switched neural networks with time delays and the inertial term [J].

Fang, Tian ;

Jiao, Shiyu ;

Fu, Dongmei ;

Su, Lei .

APPLIED MATHEMATICS AND COMPUTATION, 2021, 394

[7] An artificial neural network approach to compressor performance prediction [J].

Ghorbanian, K. ;

Gholamrezaei, M. .

APPLIED ENERGY, 2009, 86 (7-8) :1210-1221

[8] Stability and synchronization for Riemann-Liouville fractional-order time-delayed inertial neural networks [J].

Gu, Yajuan ;

Wang, Hu ;

Yu, Yongguang .

NEUROCOMPUTING, 2019, 340 :270-280

[9] Synchronization of Markov Switching Inertial Neural Networks with Mixed Delays under Aperiodically On-Off Adaptive Control [J].

Guo, Beibei ;

Xiao, Yu .

MATHEMATICS, 2023, 11 (13)

[10] Observer-based sliding mode synchronization control of complex-valued neural networks with inertial term and mixed time-varying delays [J].

Guo, Runan ;

Xu, Shengyuan .

APPLIED MATHEMATICS AND COMPUTATION, 2023, 442

← 1 2 3 4 5 →