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Circuits, Systems, and Signal Processing

, Volume 35, Issue 2, pp 651–667 | Cite as

Data Filtering-Based Multi-innovation Stochastic Gradient Algorithm for Nonlinear Output Error Autoregressive Systems

  • Yawen Mao
  • Feng DingEmail author
Short Paper

Abstract

This paper discusses the parameter estimation problems of nonlinear output error autoregressive systems and presents a data filtering-based multi-innovation stochastic gradient algorithm for improving the parameter estimation accuracy of the stochastic gradient algorithm by combining the multi-innovation identification theory and the data filtering technique. The proposed algorithm is effective and can generate highly accurate parameter estimates compared with the multi-innovation stochastic gradient algorithm. The simulation results confirm this conclusion.

Keywords

Stochastic gradient Multi-innovation identification theory  Data filtering technique Nonlinear system 

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 61273194) and the PAPD of Jiangsu Higher Education Institutions.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education)Jiangnan UniversityWuxiPeople’s Republic of China

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