Wavelet Time Shift Properties Integration with Support Vector Machines
| dc.creator | Gomez, Jaime | |
| dc.creator | Melgar, Ignacio | |
| dc.creator | Seijas, Juan | |
| dc.date | 2005-05-20 | |
| dc.date.accessioned | 2026-07-07T03:23:01Z | |
| dc.date.available | 2026-07-07T03:23:01Z | |
| dc.description | This paper presents a short evaluation about the integration of information derived from wavelet non-linear-time-invariant (non-LTI) projection properties using Support Vector Machines (SVM). These properties may give additional information for a classifier trying to detect known patterns hidden by noise. In the experiments we present a simple electromagnetic pulsed signal recognition scheme, where some improvement is achieved with respect to previous work. SVMs are used as a tool for information integration, exploiting some unique properties not easily found in neural networks. | |
| dc.description | 11 pages | |
| dc.identifier | https://arxiv.org/abs/cs/0505053 | |
| dc.identifier | http://arxiv.org/abs/cs/0505053 | |
| dc.identifier | LNAI-3131 Modeling Decisions for Artificial Intelligence, ISSN 0302-9743, p49-59, Barcelona, Spain, August-2004 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/32779 | |
| dc.subject | Information Retrieval | |
| dc.subject | Neural and Evolutionary Computing | |
| dc.title | Wavelet Time Shift Properties Integration with Support Vector Machines | |
| dc.type | text |