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Impulsive Synchronization of Stochastic Neural Networks via Controlling Partial States

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Abstract

In the paper, synchronization problem for stochastic neural networks are studied by impulsively controlling partial states. At each impulsive instant, only part of the states are controlled to realize the synchronization of impulsively coupled stochastic neural networks. By using the method of average impulsive interval, less conservative synchronization criteria are derived. The derived sufficient conditions are closely related to the parameters of system dynamics, impulsive gain, impulsive interval and the proportion of the controlled components. Finally, numerical example is given to illustrate the effectiveness of our theoretical results.

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Authors and Affiliations

  1. Department of Applied Mathematics, Nanjing Forestry University, Nanjing, 210037, People’s Republic of China

    Yuanyuan Li

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  1. Yuanyuan Li
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Correspondence to Yuanyuan Li.

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Li, Y. Impulsive Synchronization of Stochastic Neural Networks via Controlling Partial States. Neural Process Lett 46, 59–69 (2017). https://doi.org/10.1007/s11063-016-9568-0

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  • DOI: https://doi.org/10.1007/s11063-016-9568-0

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