scholarly journals Exponential synchronization of chaotic neural networks with mixed delays and impulsive effects via output coupling with delay feedback

2010 ◽  
Vol 52 (5-6) ◽  
pp. 643-653 ◽  
Author(s):  
Xiaodi Li ◽  
Martin Bohner
Keyword(s):  
Neural Networks ◽  
Exponential Synchronization ◽  
Impulsive Effects ◽  
Output Coupling ◽  
Mixed Delays ◽  
Chaotic Neural Networks

Exponential synchronization of chaotic neural networks with mixed delays

2008 ◽  
Vol 71 (13-15) ◽  
pp. 3005-3019 ◽  
Author(s):  
Tao Li ◽  
Shu-min Fei ◽  
Qing Zhu ◽  
Shen Cong
Keyword(s):  
Neural Networks ◽  
Exponential Synchronization ◽  
Mixed Delays ◽  
Chaotic Neural Networks

SYNCHRONIZATION IN AN ARRAY OF HYBRID COUPLED NEURAL NETWORKS WITH MODE-DEPENDENT MIXED DELAYS AND MARKOVIAN SWITCHING

2009 ◽  
Vol 23 (09) ◽  
pp. 1171-1187 ◽  
Author(s):  
YANG TANG ◽  
RUNHE QIU ◽  
JIAN-AN FANG
Keyword(s):  
Neural Networks ◽  
Transition Probability ◽  
Distributed Delay ◽  
Mode Switching ◽  
Mixed Delays ◽  
Time Varying ◽  
Chaotic Neural Networks ◽  
Coupled Neural Networks ◽  
Hybrid Coupling ◽  
Coupling Time

In this letter, a general model of an array of N linearly coupled chaotic neural networks with hybrid coupling is proposed, which is composed of constant coupling, time-varying delay coupling and distributed delay coupling. The complex network jumps from one mode to another according to a Markovian chain with known transition probability. Both the coupling time-varying delays and the coupling distributed delays terms are mode-dependent. By the adaptive feedback technique, several sufficient criteria have been proposed to ensure the synchronization in an array of jump chaotic neural networks with mode-dependent hybrid coupling and mixed delays in mean square. Finally, numerical simulations illustrated by mode switching between two complex networks of different structure dependent on mode switching verify the effectiveness of the proposed results.

Adaptive Synchronization in Unknown Stochastic Chaotic Neural Networks with Mixed Time-Varying Delays

2011 ◽  
pp. 289-313
Author(s):  
Jian-an Fang ◽  
Yang Tang
Keyword(s):  
Neural Networks ◽  
Sufficient Conditions ◽  
Stochastic Perturbation ◽  
Adaptive Synchronization ◽  
Output Coupling ◽  
Time Varying ◽  
Connection Weight ◽  
Chaotic Neural Networks ◽  
Simulation Results ◽  
Feedback Techniques

Neural networks (NNs) have been useful in many fields, such as pattern recognition, image processing etc. Recently, synchronization of chaotic neural networks (CNNs) has drawn increasing attention due to the high security of neural networks. In this chapter, the problem of synchronization and parameter identification for a class of chaotic neural networks with stochastic perturbation via state and output coupling, which involve both the discrete and distributed time-varying delays has been investigated. Using adaptive feedback techniques, several sufficient conditions have been derived to ensure the synchronization of stochastic chaotic neural networks. Moreover, all the connection weight matrices can be estimated while the lag synchronization and complete synchronization is achieved in mean square at the same time. The corresponding simulation results are given to show the effectiveness of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document