Abstract
In this paper, multiple windows, optimal for locally stationary processes (MW-LSP) are used to estimate the spectrogram of the electroencephalogram (EEG) where we focus on the ability to estimate transient frequency changes. A peak of known frequency was evoked in the EEG spectrum in a predetermined time interval, by using a 9 Hz flickering light. We investigate the multiple windows corresponding to the mean squared error optimal time-frequency kernel for estimation of the Wigner-Ville spectrum. The kernel is optimal for a certain locally stationary process where the covariance function is determined by two one-dimensional Gaussian functions
| Original language | English |
|---|---|
| Title of host publication | 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005 |
| Publisher | IEEE - Institute of Electrical and Electronics Engineers Inc. |
| Pages | 7293-7296 |
| Volume | 7 VOLS |
| ISBN (Print) | 0-7803-8741-4 |
| DOIs | |
| Publication status | Published - 2005 |
| Event | 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. - Shanghai, China Duration: 2005 Sept 1 → 2005 Sept 4 Conference number: 27 |
Publication series
| Name | |
|---|---|
| Volume | 7 VOLS |
| ISSN (Print) | 0589-1019 |
Conference
| Conference | 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. |
|---|---|
| Abbreviated title | IEEE-EMBS 2005 |
| Country/Territory | China |
| City | Shanghai |
| Period | 2005/09/01 → 2005/09/04 |
Subject classification (UKÄ)
- Probability Theory and Statistics
Free keywords
- Multiple windows
- Covariance function
- Locally stationary processes (MW-LSP)
- Mean squared error optimal time-frequency kernel