A Robust Support Vector Algorithm for Nonparametric Spectral Analysis

Resumen

A new approach to the nonparametric spectral estimation on the basis of the support vector method (SVM) framework is presented. A reweighted least squared 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.

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