Non-reduced order method for state estimation of quaternion-valued inertial neural networks

Author(s):  
Zhengwen Tu ◽  
Liangwei Wang ◽  
Yongxiang Zhao ◽  
Tao Peng ◽  
Xinsong Yang ◽  
...  
Author(s):  
Xuan Chen ◽  
Dongyun Lin

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.


2019 ◽  
Vol 12 (02) ◽  
pp. 1950016 ◽  
Author(s):  
Chuangxia Huang ◽  
Hua Zhang

This paper, mainly explores a class of non-autonomous inertial neural networks with proportional delays and time-varying coefficients. By combining Lyapunov function method with differential inequality approach, non-reduced order method is used to establish some novel assertions on the existence and generalized exponential stability of periodic solutions for the addressed model. In addition, an example and its numerical simulations are given to support the proposed approach.


Sign in / Sign up

Export Citation Format

Share Document