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Nuclear Norm Subspace System Identification and Its Application on a Stochastic Model of Plague

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Abstract

The discrete-time model of plague is deduced by zero-order holder based on the continuous-time model. Due to the existence of stochastic disturbances, the stochastic model is given corresponding to the discrete-time model. The state estimation and noise reduction of the stochastic model are achieved by designing Kalman filter. Nuclear norm minimization is to structure the low-rank matrix approximation instead of the singular value decomposition in the process of subspace system identification. According to the plague data from the World Health Organization, the system matrices and noise intensity of the model are identified. Simulations are carried out to show the higher approximation capability of the proposed method.

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Authors and Affiliations

  1. College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China

    Miao Yu & Jianchang Liu

  2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, 110819, China

    Miao Yu & Jianchang Liu

  3. School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, 066004, China

    Miao Yu

  4. School of Mathematics and Information Science, Anshan Normal University, Anshan, 114007, China

    Lichun Zhao

Authors
  1. Miao Yu
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  2. Jianchang Liu
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  3. Lichun Zhao
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Corresponding authors

Correspondence to Miao Yu, Jianchang Liu or Lichun Zhao.

Additional information

This research was supported by the National Natural Science Foundation of China under Grant Nos. 61374137 and 61773106, and the State Key Laboratory of Integrated Automation of Process Industry Technology and Research Center of National Metallurgical Automation Fundamental Research Funds under Grant No. 2013ZCX02-03.

This paper was recommended for publication by Editor CHEN Jie.

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Yu, M., Liu, J. & Zhao, L. Nuclear Norm Subspace System Identification and Its Application on a Stochastic Model of Plague. J Syst Sci Complex 33, 43–60 (2020). https://doi.org/10.1007/s11424-019-8003-9

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  • DOI: https://doi.org/10.1007/s11424-019-8003-9

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