Stochastic stability analysis of neutral-type impulsive neural networks with mixed time-varying delays and Markovian jumping

Authors:
Huaguang Zhang;Meng Dong;Yingchun Wang;Ning Sun
Affiliations:
School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, People's Republic of China;School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, People's Republic of China;School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, People's Republic of China;School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, People's Republic of China
Venue:
Neurocomputing
Year:
2010

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Abstract

In this paper, the stochastic stability problem of neutral-type impulsive neural networks (NINNs) with mixed time-varying delays and Markovian jumping is investigated. By utilizing the Lyapunov-Krasovkii functional approach and linear matrix inequality (LMI) technique, we obtain some novel globally exponentially stable results. Delay-dependent sufficient condition for the above problem is obtained, which is usually less conservative than delay-independent ones. An example is given to show the effectiveness of the obtained results.