Global polynomial stabilization and global asymptotic stabilization of coupled neural networks with multi‐proportional delays

2020 ◽  
Vol 43 (12) ◽  
pp. 7345-7360
Author(s):  
Rui Zhou ◽  
Liqun Zhou
Keyword(s):  
Neural Networks ◽  
Asymptotic Stabilization ◽  
Coupled Neural Networks ◽  
Global Asymptotic Stabilization ◽  
Proportional Delays ◽  
Polynomial Stabilization

Synchronization of semi-Markov coupled neural networks with impulse effects and leakage delay

2020 ◽  
Vol 386 ◽  
pp. 221-231 ◽  
Author(s):  
S.A. Karthick ◽  
R. Sakthivel ◽  
Faris Alzahrani ◽  
A. Leelamani
Keyword(s):  
Neural Networks ◽  
Leakage Delay ◽  
Coupled Neural Networks

Stabilization for a class of delayed switched inertial neural networks via non-reduced order method

2021 ◽  
pp. 014233122098594
Author(s):  
Xuan Chen ◽  
Dongyun Lin
Keyword(s):  
Neural Networks ◽  
Comparative Research ◽  
Lyapunov Functional ◽  
Sufficient Conditions ◽  
Global Stabilization ◽  
Order Method ◽  
Reduced Order ◽  
Global Asymptotic Stabilization ◽  
Inertial Neural Networks ◽  
Barbalat Lemma

This paper tackles the issue of global stabilization for a class of delayed switched inertial neural networks (SINN). Distinct from the frequently employed reduced-order technique, this paper studies SINN directly through non-reduced order method. By constructing a novel Lyapunov functional and using Barbalat Lemma, sufficient conditions for the global asymptotic stabilization issue and global exponential stabilization issue of the considered SINN are established. Numerical simulations further confirm the feasibility of the main results. The comparative research shows that global stabilization results of this paper complement and improve some existing work.

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