Cargando…
Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso
Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs). Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wr...
| Autores principales: | , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi Publishing Corporation
2015
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4354735/ https://www.ncbi.nlm.nih.gov/pubmed/25802861 http://dx.doi.org/10.1155/2015/703768 |