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Identification Methods for Two-Variable Difference Systems

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Abstract

This paper proposes two identification methods for two-variable difference systems. The output and the input of the two-variable difference systems depend not only on time but also on spatial coordinates. A recursive least squares algorithm and a stochastic gradient algorithm are introduced to estimate the unknown parameters. Furthermore, in order to increase the convergence rate and to decrease the computational effort, a forgetting factor stochastic gradient algorithm is proposed. The simulation results indicate that the proposed methods are effective.

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Author information

Authors and Affiliations

  1. School of Internet of Things Engineering, Jiangnan University, Wuxi, 214122, People’s Republic of China

    Jing Chen

  2. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, People’s Republic of China

    Bin Jiang

Authors
  1. Jing Chen
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  2. Bin Jiang
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Corresponding author

Correspondence to Jing Chen.

Additional information

This work was supported by the National Natural Science Foundation of China (Nos. 61403165, 61304138), the Natural Science Foundation of Jiangsu Province (Nos. BK20131109, BK20130163) and the Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province (No. 2014SJD381).

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Chen, J., Jiang, B. Identification Methods for Two-Variable Difference Systems. Circuits Syst Signal Process 35, 3027–3039 (2016). https://doi.org/10.1007/s00034-015-0182-6

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  • DOI: https://doi.org/10.1007/s00034-015-0182-6

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