A Novel Flexible Model for the Extraction of Features from Brain Signals in the Time-Frequency Domain
Electrophysiological signals such as the EEG, MEG, or LFPs have been extensively studied over the last decades, and elaborate signal processing algorithms have been developed for their analysis. Many of these methods are based on time-frequency decomposition to account for the signals’ spectral prop...
Saved in:
| Main Authors: | R. Heideklang, G. Ivanova |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
|
| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2013/759421 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Corrigendum to “Comparison of Matrix Pencil Extracted Features in Time Domain and in Frequency Domain for Radar Target Classification”
by: Mahmoud Khodjet-Kesba, et al.
Published: (2015-01-01) -
A New Time-frequency Domain Feature Extraction Method for Rolling Bearing Fault Diagnosis
by: Chen Junjie, et al.
Published: (2016-01-01) -
Nonlinear time domain and multi-scale frequency domain feature fusion for time series forecasting
by: Kejiang Xiao, et al.
Published: (2025-08-01) -
Continuous Time Frequency Domain Analysis of Ф-OTDR Nonstationary Signals
by: XU Tao, et al.
Published: (2021-08-01) -
Optimized Time-domain Feature Extraction for Early Onset Diagnosis of Parkinson Disease From EEG Signals
by: Delshad Ghavami, et al.
Published: (2025-07-01)