Upgrading Pulse Detection with Time Shift Properties Using Wavelets and Support Vector Machines
<|reference_start|>Upgrading Pulse Detection with Time Shift Properties Using Wavelets and Support Vector Machines: Current approaches in pulse detection use domain transformations so as to concentrate frequency related information that can be distinguishable from noise. In real cases we do not know when the pulse will begin, so we need a time search process in which time windows are scheduled and analysed. Each window can contain the pulsed signal (either complete or incomplete) and / or noise. In this paper a simple search process will be introduced, allowing the algorithm to process more information, upgrading the capabilities in terms of probability of detection (Pd) and probability of false alarm (Pfa).<|reference_end|>
@article{gomez2005upgrading,
    title={Upgrading Pulse Detection with Time Shift Properties Using Wavelets and
  Support Vector Machines},
    author={Jaime Gomez, Ignacio Melgar, Juan Seijas},
    journal={Proceedings of the World Automation Congress (WAC-04), Sevilla,
  Spain, June-2004},
    year={2005},
    archivePrefix={arXiv},
    eprint={cs/0505052},
    primaryClass={cs.IR cs.NE}
}