Support vector method for robust ARMA system identification

  title={Support vector method for robust ARMA system identification},
  author={Jos{\'e} Luis Rojo-{\'A}lvarez and Luis Mart{\'i}nez-Ram{\'o}n and Mario de Prado-Cumplido and Antonio Art{\'e}s-Rodr{\'i}guez and An{\'i}bal R. Figueiras-Vidal},
  journal={IEEE Transactions on Signal Processing},
This paper presents a new approach to auto-regressive and moving average (ARMA) modeling based on the support vector method (SVM) for identification applications. A statistical analysis of the characteristics of the proposed method is carried out. An analytical relationship between residuals and SVM-ARMA coefficients allows the linking of the fundamentals of SVM with several classical system identification methods. Additionally, the effect of outliers can be cancelled. Application examples show… CONTINUE READING
Highly Cited
This paper has 91 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 48 extracted citations

92 Citations

Citations per Year
Semantic Scholar estimates that this publication has 92 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 19 references

Heart rate variability. Standards of measurement, physiological interpretation and clinical use

  • Task force of the European Society of Cardiology, the North American Society of Pacing, Electrophysiology
  • Eur. Heart J., vol. 17, pp. 354–381, Mar. 1996.
  • 1996
Highly Influential
5 Excerpts

An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods

  • N. Cristianini, J. S. Taylor
  • 2000
1 Excerpt

GPS time series modeling by autoregressive moving average method: Application to the crustal deformation in central Japan

  • J. Li, K. Miyashita, T. Kato, S. Miyazaki
  • Earth Planets Space, vol. 52, pp. 155–162, Feb…
  • 2000
1 Excerpt

Similar Papers

Loading similar papers…