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A Recursive Least Squares Algorithm for Pseudo-Linear ARMA Systems Using the Auxiliary Model and the Filtering Technique

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Abstract

In this paper, we study the parameter estimation problem for pseudo-linear autoregressive moving average systems. The key is to use the data filtering technique to obtain a pseudo-linear identification model and to derive an auxiliary model-based recursive least squares algorithm through filtering the observation data. The simulation results confirm the effectiveness of the proposed algorithm.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 61304138), the Natural Science Foundation of Jiangsu Province (China, BK20130163) and the PAPD of Jiangsu Higher Education Institutions.

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Authors and Affiliations

  1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, 214122, People’s Republic of China

    Lanjie Guo, Yanjiao Wang & Cheng Wang

Authors
  1. Lanjie Guo
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  2. Yanjiao Wang
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  3. Cheng Wang
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Correspondence to Lanjie Guo.

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Guo, L., Wang, Y. & Wang, C. A Recursive Least Squares Algorithm for Pseudo-Linear ARMA Systems Using the Auxiliary Model and the Filtering Technique. Circuits Syst Signal Process 35, 2655–2667 (2016). https://doi.org/10.1007/s00034-015-0164-8

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