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Paper data
Adaptive SVC for nonlinear channel equalization

Pérez-Cruz Fernando, DTSC Universidad Carlos III de Madrid
Artes-Rodriguez Antonio, DTSC Universidad Carlos III de Madrid

Page numbers in the proceedings:
Volume II pp 45-48

Non linear Techniques for Channel Equalization (1/2)

Paper abstract
We propose a new scheme for adapting support vector classifiers (SVC) in non-stationary environments. This adaptive SVC (ASVC) relies in interpreting the margin and penalty factor of the SVC as a relevance measure over the samples and on an iterative re-weighted least square (IRWLS) approach for optimizing it, which resembles the RLS filtering for adaptive equalization. The ASVC capabilities are shown by means of computer experiments.

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