Sub-Optimum Signal Linear Detector Using Wavelets and Support Vector Machines
Information Retrieval
2007-05-23 v1 Neural and Evolutionary Computing
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.
Cite
@article{arxiv.cs/0505051,
title = {Sub-Optimum Signal Linear Detector Using Wavelets and Support Vector Machines},
author = {Jaime Gomez and Ignacio Melgar and Juan Seijas and Diego Andina},
journal= {arXiv preprint arXiv:cs/0505051},
year = {2007}
}
Comments
6 pages