Finite‐Time Synchronization of Complex‐Valued Delayed Neural Networks with Discontinuous Activations

2018 ◽  
Vol 20 (6) ◽  
pp. 2237-2247 ◽  
Author(s):  
Enli Wu ◽  
Xinsong Yang ◽  
Chen Xu ◽  
Fuad E. Alsaadi ◽  
Tasawar Hayat
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Delayed Neural Networks ◽  
Discontinuous Activations ◽  
Complex Valued

scholarly journals Finite-Time Projective Synchronization of Caputo Type Fractional Complex-Valued Delayed Neural Networks

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1406
Author(s):  
Shuang Wang ◽  
Hai Zhang ◽  
Weiwei Zhang ◽  
Hongmei Zhang
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Adaptive Controller ◽  
Projective Synchronization ◽  
Numerical Examples ◽  
Delayed Neural Networks ◽  
Response Systems ◽  
Inequality Techniques ◽  
Complex Valued

This paper focuses on investigating the finite-time projective synchronization of Caputo type fractional-order complex-valued neural networks with time delay (FOCVNNTD). Based on the properties of fractional calculus and various inequality techniques, by constructing suitable the Lyapunov function and designing two new types controllers, i.e., feedback controller and adaptive controller, two sufficient criteria are derived to ensure the projective finite-time synchronization between drive and response systems, and the synchronization time can effectively be estimated. Finally, two numerical examples are presented to verify the effectiveness and feasibility of the proposed results.

Finite-Time Synchronization of Complex-Valued Neural Networks with Mixed Delays and Uncertain Perturbations

2017 ◽  
Vol 46 (1) ◽  
pp. 271-291 ◽  
Author(s):  
Chao Zhou ◽  
Wanli Zhang ◽  
Xinsong Yang ◽  
Chen Xu ◽  
Jianwen Feng
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Mixed Delays ◽  
Complex Valued

scholarly journals New Methods of Finite-Time Synchronization for a Class of Fractional-Order Delayed Neural Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Weiwei Zhang ◽  
Jinde Cao ◽  
Ahmed Alsaedi ◽  
Fuad E. Alsaadi
Keyword(s):  
Neural Networks ◽  
Fractional Order ◽  
Finite Time ◽  
Time Synchronization ◽  
Sufficient Conditions ◽  
Time Interval ◽  
Finite Time Interval ◽  
Delayed Neural Networks ◽  
New Methods ◽  
Theoretical Results

Finite-time synchronization for a class of fractional-order delayed neural networks with fractional order α, 0<α≤1/2 and 1/2<α<1, is investigated in this paper. Through the use of Hölder inequality, generalized Bernoulli inequality, and inequality skills, two sufficient conditions are considered to ensure synchronization of fractional-order delayed neural networks in a finite-time interval. Numerical example is given to verify the feasibility of the theoretical results.

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