Finite -time synchronization;
Fuzzy system;
Memristive neural network;
Time delay;
Fuzzy control;
Pseudorandom number generator;
STABILITY;
IDENTIFICATION;
SYSTEMS;
D O I:
10.1016/j.fss.2022.10.013
中图分类号:
TP301 [理论、方法];
学科分类号:
081202 ;
摘要:
This paper focuses on the study of synchronization problem for T-S fuzzy memristive neural networks with time delay. First, a delay-independent nonlinear fuzzy control is designed. Second, under the designed fuzzy control, two kinds of finite-time synchro-nization criteria are obtained by comparison method and Lyapunov function method, respectively. Furthermore, the settling time is estimated. Finally, a numerical simulation example is provided to demonstrate the effectiveness and feasibility of the theoretical results, and an application of the obtained theories is also given in the pseudorandom number generator (PRNG).(c) 2022 Elsevier B.V. All rights reserved.
机构:
Hubei Key Laboratory of Optical Information and Pattern Recognition, School of Electrical and Information Engineering,Wuhan Institute of TechnologyHubei Key Laboratory of Optical Information and Pattern Recognition, School of Electrical and Information Engineering,Wuhan Institute of Technology
机构:
City Univ Hong Kong, Dept Mech & Biomed Engn, Kowloon, Hong Kong, Peoples R ChinaCity Univ Hong Kong, Dept Mech & Biomed Engn, Kowloon, Hong Kong, Peoples R China
Li, Yue
Liu, Lu
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机构:
City Univ Hong Kong, Dept Mech & Biomed Engn, Kowloon, Hong Kong, Peoples R ChinaCity Univ Hong Kong, Dept Mech & Biomed Engn, Kowloon, Hong Kong, Peoples R China
Liu, Lu
Feng, Gang
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机构:
City Univ Hong Kong, Dept Mech & Biomed Engn, Kowloon, Hong Kong, Peoples R ChinaCity Univ Hong Kong, Dept Mech & Biomed Engn, Kowloon, Hong Kong, Peoples R China