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Exponential Synchronization of Stochastic Memristive Neural Networks with Time-Varying Delays

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Abstract

This paper pays attention to the synchronization control methodology for stochastic memristive system. On the framework of Lyapunov functional, stability theory and free-weighting matrices technique, some brand-new solvability criteria are established to ensure the exponential synchronization goal of the target model. Considering the introduce of some free-weighting matrices, the obtained synchronization verdict will be much more applicable. Finally, the living example is included to show the effectiveness of the presented methodology.

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Authors and Affiliations

  1. School of Mathematics and Information Science, Shaanxi Normal University, Xi’an, 710062, China

    Ruoxia Li & Xingbao Gao

  2. The Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, and School of Mathematics, Southeast University, Nanjing, 211189, China

    Jinde Cao

Authors
  1. Ruoxia Li
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  2. Xingbao Gao
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  3. Jinde Cao
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Correspondence to Xingbao Gao.

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The authors declare that they have no conflict of interest.

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This work was supported by National Natural Science Foundation of China (Grant Nos. 61803247, 61802243, 61273311 and 61173094), Project Funded by China Postdoctoral Science Foundation 2018M640948, the Fundamental Research Funds for the Central Universities under Grant No. GK201903003, the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence under Grant No. BM2017002.

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Li, R., Gao, X. & Cao, J. Exponential Synchronization of Stochastic Memristive Neural Networks with Time-Varying Delays. Neural Process Lett 50, 459–475 (2019). https://doi.org/10.1007/s11063-019-09989-5

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  • DOI: https://doi.org/10.1007/s11063-019-09989-5

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