A robust support vector algorithm for nonparametric spectral analysis

Author

Rojo-Álvarez, José Luis ; Martínez-Ramón, Manel ; Figueiras-Vidal, Aníbal R. ; García-Armada, Ana ; Artés-Rodríguez, AndAntonio

Author_Institution

Dept. of Signal Theor. & Commun., Univ. Carlos III de Madrid, Leganes, Spain

Volume

10

Issue

11

fYear

2003

Firstpage

320

Lastpage

323

Abstract

We present a new approach to nonparametric spectral estimation on the basis of the support vector method (SVM). A reweighted least squares error formulation avoids the computational limitations of quadratic programming. The application to a synthetic example and to a digital communication problem shows the robustness of the SVM spectral analysis algorithm.

Keywords

channel estimation; digital subscriber lines; impulse noise; learning automata; least squares approximations; spectral analysis; ADSL channel estimation; SVM; impulsive noise; nonparametric spectral analysis; nonparametric spectral estimation; quadratic programming; reweighted least squares error formulation; support vector algorithm; support vector method; Communication systems; Cost function; Fourier transforms; Iterative algorithms; Least squares methods; Quadratic programming; Robustness; Spectral analysis; Support vector machine classification; Support vector machines;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2003.818866

Filename

1237627