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Li, Yingwei; Guo, Xueqing

Exponential synchronization for stochastic neural networks with mixed time delays and Markovian jump parameters via sampled data. (English) Zbl 1406.93304

Abstr. Appl. Anal. 2014, Article ID 505164, 17 p. (2014).
Summary: The exponential synchronization issue for stochastic neural networks (SNNs) with mixed time delays and Markovian jump parameters using sampled-data controller is investigated. Based on a novel Lyapunov-Krasovskii functional, stochastic analysis theory, and linear matrix inequality (LMI) approach, we derived some novel sufficient conditions that guarantee that the master systems exponentially synchronize with the slave systems. The design method of the desired sampled-data controller is also proposed. To reflect the most dynamical behaviors of the system, both Markovian jump parameters and stochastic disturbance are considered, where stochastic disturbances are given in the form of a Brownian motion. The results obtained in this paper are a little conservative comparing the previous results in the literature. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.

MSC:

93E03 Stochastic systems in control theory (general)
68T05 Learning and adaptive systems in artificial intelligence
93C57 Sampled-data control/observation systems

Keywords:

stochastic neural networks; Markovian jump; sampled data; exponential synchronization
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\textit{Y. Li} and \textit{X. Guo}, Abstr. Appl. Anal. 2014, Article ID 505164, 17 p. (2014; Zbl 1406.93304)
Full Text: DOI

References:

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