Super-resolution time-frequency maps
Version 3.0.0.0 (653 KB) by
Andrei Barborica
Increases resolution of time-frequency maps by combining CWT maps for different Q-factors and rotations (chirplets) of the mother wavelet
Computes the combinations of multiple sets of continuous wavelet transforms (time-frequency maps) obtained for different quality factors Qf of the Gabor mother wavelet as well as for different rotations in the time-frequency space of the mother wavelet (chirplets). By combining the set of wavelet transforms using different projection methods, the resolution of the resulting time-frequency map is increased. The projection methods include averaging (default), minimum intensity projection, maximum intensity projection, geometric mean, and quantiles. Can be applied to creating super-resolution time-frequency maps of electroencephalographic (EEG) or other types of signals.
Cite As
Andrei Barborica (2026). Super-resolution time-frequency maps (https://www.mathworks.com/matlabcentral/fileexchange/57348-super-resolution-time-frequency-maps), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Created with
R2023a
Compatible with R2014b and later releases
Platform Compatibility
Windows macOS LinuxCategories
- Sciences > Neuroscience > Human Brain Mapping > EEG/MEG/ECoG >
- Sciences > Neuroscience > Frequently-used Algorithms >
- Signal Processing > Wavelet Toolbox > Time-Frequency Analysis > Continuous Wavelet Transforms >
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| Version | Published | Release Notes | |
|---|---|---|---|
| 3.0.0.0 | Updated to support chirplets, quantiles and geometric mean as projection methods |
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| 2.0.0.0 | Implemented support for different projection methods, using optional 'Method' name-value pair, that can take the values 'Average' (default), 'MinIP' and 'MIP'. 'MinIP' is a "hard" projection method while 'Average' can be considered a "soft" method. |
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| 1.0.0.0 | Added a script QCWTDemo.m and sample EEG data illustrating the use of the function.
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