Feature Extraction by Mutual Information Based on Minimal-Redundancy-Maximal-Relevance Criterion and Its Application to Classifying EEG Signal for Brain-Computer Interfaces
None
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2011
|
| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/13494 |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares: Feature Extraction by Mutual Information Based on Minimal-Redundancy-Maximal-Relevance Criterion and Its Application to Classifying EEG Signal for Brain-Computer Interfaces
- Nonlinear Independent Component Analysis for EEG-Based Brain-Computer Interface Systems
- Feature Selection for Transient Stability Assessment Based on Improved Maximal Relevance and Minimal Redundancy Criterion
- MaxMI: A Maximal Mutual Information Criterion for Manipulation Concept Discovery
- Multiclass Common Spatial Pattern for EEG based Brain Computer Interface with Adaptive Learning Classifier
- Generating minimal redundant and maximal irredundant sets in incidence graphs
- Active Feature Selection for the Mutual Information Criterion