Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/27975
Title: Distributed synchronization of coupled neural networks via randomly occurring control
Authors: Tang, Y
Wong, WK 
Keywords: Bernoulli stochastic variables
Complex dynamical networks
Pinning control
Randomly occurring control
Stochastic disturbances
Issue Date: 2013
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on neural networks and learning systems, 2013, v. 24, no. 3, p. 435-447 How to cite?
Journal: IEEE transactions on neural networks and learning systems 
Abstract: In this paper, we study the distributed synchronization and pinning distributed synchronization of stochastic coupled neural networks via randomly occurring control. Two Bernoulli stochastic variables are used to describe the occurrences of distributed adaptive control and updating law according to certain probabilities. Both distributed adaptive control and updating law for each vertex in a network depend on state information on each vertex's neighborhood. By constructing appropriate Lyapunov functions and employing stochastic analysis techniques, we prove that the distributed synchronization and the distributed pinning synchronization of stochastic complex networks can be achieved in mean square. Additionally, randomly occurring distributed control is compared with periodically intermittent control. It is revealed that, although randomly occurring control is an intermediate method among the three types of control in terms of control costs and convergence rates, it has fewer restrictions to implement and can be more easily applied in practice than periodically intermittent control.
URI: http://hdl.handle.net/10397/27975
ISSN: 2162-237X
EISSN: 2162-2388
DOI: 10.1109/TNNLS.2012.2236355
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