Robust exponential stability of cellular neural networks with mode-dependent time delays and Markovian jump parameters

In this paper, we investigate the problem of global robust exponential stability for a class of cellular neural networks with mode-dependent time-varying delays and Markovian jump parameters by employing an improved free-weighting matrix approach. A new Markov process as discrete-time, discrete-stat...

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Bibliographic Details
Main Authors: Ji-Qing Qiu, Kun-Feng Lu, Jie Li
Format: Conference Proceeding
Language:English
Subjects:
Cellular neural networks
Cybernetics
Delay effects
discrete-time system
Machine learning
Markovian jumping system
mode-dependent time delays
robust exponential stability
Robust stability
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Summary:In this paper, we investigate the problem of global robust exponential stability for a class of cellular neural networks with mode-dependent time-varying delays and Markovian jump parameters by employing an improved free-weighting matrix approach. A new Markov process as discrete-time, discrete-state Markov process are considered. A mode-dependent time delays stability performance analysis result is first established for error systems without ignoring any terms in the derivative of Lyapunov functional by considering the relationship between the time-varying delay and its upper bound. Finally, one numerical example illustrate the effectiveness and less conservativeness of our proposed method.
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212560