Mode-Dependent Stochastic Synchronization for Markovian Coupled Neural Networks With Time-Varying Mode-Delays

This paper investigates the stochastic synchronization problem for Markovian hybrid coupled neural networks with interval time-varying mode-delays and random coupling strengths. The coupling strengths are mutually independent random variables and the coupling configuration matrices are nonsymmetric....

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Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems 2015-11, Vol.26 (11), p.2621-2634
Main Authors: Zhang, Huaguang, Wang, Junyi, Wang, Zhanshan, Liang, Hongjing
Format: Article
Language:English
Subjects:
Complex networks
Computer Simulation
Couplings
Criteria
Extended Jensen's integral inequality
Integrals
Joining
Linear matrix inequalities
Markov Chains
Markov processes
Markovian coupled neural networks
mode-dependant augmented Lyapunov-Krasovskii functional (LKF)
Neural networks
Neural Networks (Computer)
Random variables
Stochastic Processes
stochastic synchronization
Strength
Synchronism
Synchronization
Time Factors
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Summary:This paper investigates the stochastic synchronization problem for Markovian hybrid coupled neural networks with interval time-varying mode-delays and random coupling strengths. The coupling strengths are mutually independent random variables and the coupling configuration matrices are nonsymmetric. A mode-dependent augmented Lyapunov-Krasovskii functional (LKF) is proposed, where some terms involving triple or quadruple integrals are considered, which makes the LKF matrices mode-dependent as much as possible. This gives significant improvement in the synchronization criteria, i.e., less conservative results can be obtained. In addition, by applying an extended Jensen's integral inequality and the properties of random variables, new delay-dependent synchronization criteria are derived. The obtained criteria depend not only on upper and lower bounds of mode-delays but also on mathematical expectations and variances of the random coupling strengths. Finally, two numerical examples are provided to demonstrate the feasibility of the proposed results.
ISSN:2162-237X
2162-2388
DOI:10.1109/TNNLS.2014.2387885