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


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.


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



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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