Enhanced Global Asymptotic Stabilization Criteria for Delayed Fractional Complex-valued Neural Networks with Parameter Uncertainty

2019 ◽  
Vol 17 (4) ◽  
pp. 880-895 ◽  
Author(s):  
Xiaohong Wang ◽  
Zhen Wang ◽  
Yingjie Fan ◽  
Jianwei Xia ◽  
Hao Shen
Keyword(s):  
Neural Networks ◽  
Parameter Uncertainty ◽  
Asymptotic Stabilization ◽  
Global Asymptotic Stabilization ◽  
Complex Valued

Complex-valued Neural Networks

2011 ◽  
Vol 131 (1) ◽  
pp. 2-8
Author(s):  
Akira Hirose
Keyword(s):  
Neural Networks ◽  
Complex Valued

Stochastic Complex-valued Neural Networks for Radar

2021 ◽  
Author(s):  
Othmane-Latif Ouabi ◽  
Radmila Pribic ◽  
Sorin Olaru
Keyword(s):  
Neural Networks ◽  
Complex Valued

scholarly journals Finite-time projective synchronization of stochastic complex-valued neural networks with probabilistic time-varying delays

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Meng Hui ◽  
Jiahuang Zhang ◽  
Jiao Zhang ◽  
Herbert Ho-Ching Iu ◽  
Rui Yao ◽  
...  
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Projective Synchronization ◽  
Time Varying ◽  
Complex Valued

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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