Continuous wavelet transform for time series using multiple Q-factor Gabor wavelets

Version 2.0.0.0 (280 KB) von Andrei Barborica
Increases resolution of time-frequency maps by combining CWTs for different Q-factors
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Aktualisiert 29. Mär 2017

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Computes the absolute value of the complex continuous wavelet coefficients for the time series x sampled at frequency Fs, at the frequency values in the Fw vector using Gabor wavelets having quality factors Qf . By combining the set of wavelet transforms using different projection methods, the resolution of the resulting wavelet transform is increased. The projection methods include averaging (default), minimum intensity projection and maximum intensity projection. Can be applied to obtaining super-resolution time-frequency maps of EEG signals.

Zitieren als

Andrei Barborica (2025). Continuous wavelet transform for time series using multiple Q-factor Gabor wavelets (https://de.mathworks.com/matlabcentral/fileexchange/57348-continuous-wavelet-transform-for-time-series-using-multiple-q-factor-gabor-wavelets), MATLAB Central File Exchange. Abgerufen.

Kompatibilität der MATLAB-Version
Erstellt mit R2014b
Kompatibel mit allen Versionen
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Version Veröffentlicht Versionshinweise
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.
1.0.0.0

Added a script QCWTDemo.m and sample EEG data illustrating the use of the function.
Added example of use and thumbnail