Support Vector Method for Robust ARMA System Identification


Abstract:

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 the performance of SVM-ARMA algorithm when it is compared with other system identification methods.

Año de publicación:

2004

Keywords:

  • ARMA modeling
  • TIME SERIES
  • Cross-correlation
  • Support vector method
  • system identification

Fuente:

scopusscopus

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Optimización matemática
  • Aprendizaje automático
  • Modelo estadístico

Áreas temáticas:

  • Métodos informáticos especiales