Exponential synchronization of delayed neural networks involving unmeasurable neuron states via impulsive observer and impulsive control

2021 ◽  
Vol 441 ◽  
pp. 13-24
Author(s):  
Yuhan Wang ◽  
Xiaodi Li ◽  
Shiji Song
Keyword(s):  
Neural Networks ◽  
Impulsive Control ◽  
Exponential Synchronization ◽  
Delayed Neural Networks

Exponential synchronization of stochastic perturbed chaotic delayed neural networks

2007 ◽  
Vol 70 (13-15) ◽  
pp. 2477-2485 ◽  
Author(s):  
Yonghui Sun ◽  
Jinde Cao ◽  
Zidong Wang
Keyword(s):  
Neural Networks ◽  
Exponential Synchronization ◽  
Delayed Neural Networks

scholarly journals Synchronization of Chaotic Delayed Neural Networks via Impulsive Control

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Yang Fang ◽  
Kang Yan ◽  
Kelin Li
Keyword(s):  
Neural Networks ◽  
Impulsive Control ◽  
Sufficient Conditions ◽  
Stability Theorem ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Lyapunov Stability Theorem ◽  
Delayed Neural Networks ◽  
Impulsive Synchronization ◽  
Synchronization Problem

This paper is concerned with the impulsive synchronization problem of chaotic delayed neural networks. By employing Lyapunov stability theorem, impulsive control theory and linear matrix inequality (LMI) technique, several new sufficient conditions ensuring the asymptotically synchronization for coupled chaotic delayed neural networks are derived. Based on these new sufficient conditions, an impulsive controller is designed. Moreover, the stable impulsive interval of synchronized neural networks is objectively estimated by combining the MATLAB LMI toolbox and one of the two given equations. Two examples with numerical simulations are given to illustrate the effectiveness of the proposed method.

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