Article ID Journal Published Year Pages File Type
411881 Neurocomputing 2015 8 Pages PDF
Abstract

This paper studies the problem of finite-time H∞H∞ synchronization control for semi-Markov jump delayed neural networks with randomly occurring uncertainties. The randomly occurring parameter uncertainties follow certain mutually uncorrelated Bernoulli distributed white noise sequences. By employing a Markov switching Lyapunov functional and a weak infinitesimal operator, a criterion is obtained to ensure that the resulting error system is stochastically finite-time stable and master system synchronizes with the slave system over a finite-time interval accordingly. Based on this, a clear expression for the desired controller is given by using a simple matrix decoupling. The effectiveness of the proposed method is demonstrated by employing a simulation example.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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