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

Versione 2.0.0.0 (280 KB) da Andrei Barborica
Increases resolution of time-frequency maps by combining CWTs for different Q-factors
5.0
(4)
994 download
Aggiornato 29 mar 2017

Visualizza la licenza

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.

Cita come

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

Compatibilità della release di MATLAB
Creato con R2014b
Compatibile con qualsiasi release
Compatibilità della piattaforma
Windows macOS Linux
Tag Aggiungi tag

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Versione Pubblicato Note della release
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