Name
Abstract | ||
|---|---|---|
A methodology for wavelet synthesis based on lifting scheme and genetic algorithms is presented. Often, the wavelet synthesis is addressed to solve the problem of choosing properly a wavelet function from an existing library, but which may be not specially designed to the application in hand. The task under consideration is the identification of epileptic seizures over electroencephalogram recordings. Although basic classifiers are employed, results rendered that the proposed methodology is successful in the considered study achieving similar classification rates that had been reported in literature. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IEMBS.2011.6090735 | EMBC |
Keywords | Field | DocType |
wavelet transforms,wavelet synthesis,electroencephalography,medical signal processing,lifting scheme,electroencephalogram recordings,optimized wavelet decomposition,genetic algorithm,genetic algorithms,eeg seizure identification,epileptic seizures,feature extraction,wavelet transform,vectors,optimization,principal component analysis | Wavelet decomposition,Pattern recognition,Lifting scheme,Computer science,Speech recognition,Feature extraction,Artificial intelligence,Electroencephalography,Principal component analysis,Genetic algorithm,Wavelet transform,Wavelet | Conference |
Volume | ISSN | ISBN |
2011 | 1557-170X | 978-1-4244-4122-8 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pinzon-Morales, R.D. | 1 | 1 | 0.69 |
| Álvaro Orozco-Gutiérrez | 2 | 5 | 2.46 |
| G Castellanos-Dominguez | 3 | 12 | 4.98 |