Stability analysis on state-dependent impulsive Hopfield neural networks via fixed-time impulsive comparison system method

2018 ◽  
Vol 316 ◽  
pp. 20-29 ◽  
Author(s):  
Yinghua Zhou ◽  
Chuandong Li ◽  
Hui Wang
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Fixed Time ◽  
Hopfield Neural Networks ◽  
Comparison System ◽  
State Dependent ◽  
System Method

scholarly journals The Fast Fixed-Time Bipartite Synchronization of Coupled Delayed Neural Networks with Signed Graphs

2021 ◽  
Author(s):  
Shiju Yang ◽  
Chuandong Li ◽  
Yu Li ◽  
Ting Yang ◽  
Bo Li
Keyword(s):  
Neural Networks ◽  
Time Synchronization ◽  
Lyapunov Stability Theory ◽  
Fixed Time ◽  
Initial Condition ◽  
Signed Graphs ◽  
Comparison System ◽  
Delayed Neural Networks ◽  
Synchronization Problem ◽  
System Method

Abstract In this paper, the fixed-time bipartite synchronization problem for coupled delayed neural networks with signed graphs is discussed. Different from traditional neural networks, the interactions between nodes of delayed neural networks can be either collaborative or antagonistic. Furthermore, compared with the initial-condition based finite-time synchronization, the settling time is bounded by a constant within fixedtime regardless of the initial condition. It is worth noting that the fixed-time stable network for bipartite synchronization in this paper achieves more faster convergence than most existing publications. By applying constructing comparison system method, Lyapunov stability theory and inequality techniques, some sufficient criteria for fixed-time bipartite synchronization are obtained. Finally, two numerical examples are granted to display the performance of the obtained results.

Stability analysis of delayed Hopfield Neural Networks with impulses via inequality techniques

2015 ◽  
Vol 158 ◽  
pp. 281-294 ◽  
Author(s):  
Adnène Arbi ◽  
Chaouki Aouiti ◽  
Farouk Chérif ◽  
Abderrahmane Touati ◽  
Adel M. Alimi
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Hopfield Neural Networks ◽  
Inequality Techniques
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