| Título: | Electroencephalography Feature Extraction Using High Time-Frequency Resolution Analysis |
| Autores: |
Shao-bai, Zhang; Nanjing University of Posts and Telecommunications Dan-dan, Huang; Nanjing University of Posts and Telecommunications |
| Fecha: | 2012-10-01 |
| Publicador: | TELKOMNIKA: Indonesian journal of electrical engineering |
| Fuente: |
 |
| Tipo: |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| Tema: | No aplica |
| Descripción: | The way to analyze EEG signals is mainly the method of time-frequency analysis, which cross terms and resolution are two contradictory factors. However, the high time-frequency resolution analysis (HTFRA) can combine both of them. The HTFRA is based on the Wigner-Ville distribution and effectively eliminate the cross of Wigner-Ville distribution without affecting the signal resolution by using the Median Affined Filter MAF method for nonlinear filtering. The simulated signals are analyzed with Short-Time Fourier Transform, Wigner-Ville distribution, and HTFRA, respectively. The results indicate that HTFRA give a better energy distribution in the time-frequency field compared with the traditional methods. |
| Idioma: | Inglés |