Sub-Optimum Signal Linear Detector Using Wavelets and Support Vector Machines
Jaime Gomez, Ignacio Melgar, Juan Seijas, Diego Andina
Abstract
The problem of known signal detection in Additive White Gaussian Noise is considered. In previous work, a new detection scheme was introduced by the authors, and it was demonstrated that optimum performance cannot be reached in a real implementation. In this paper we analyse Support Vector Machines (SVM) as an alternative, evaluating the results in terms of Probability of detection curves for a fixed Probability of false alarm.
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