Comments (5)
Hi Whip123,
In the article I used the Morse wavelet to mimic the Morlet Wavelet as close as possible:
[wt,freqs] = cwt(data,'morse',fs,'FrequencyLimits',[f0 f1],'VoicesPerOctave',4,'WaveletParameters',[floor(bandwidth/40) bandwidth]);
image(abs(wt),"CDataMapping","scaled")
where fs
is the sample frequency, f0
and f1
are the start and end of the frequency range, respectively, and bandwidth
the sigma.
Does this answer your question?
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Hi fastlib,
Yeah, the comment is immensely helpful.
However, I am still a bit confused about how did you determine the parameters of the Morse Wavelet will have the same response as the Morlet Wavelet?
Bandwidth = 20
[wt,cwtf] = cwt(signal,'morse',fs,'FrequencyLimits',[0.25 20],'VoicesPerOctave',48,'WaveletParameters',[floor(bandwidth/40) bandwidth]);
Furthermore, just want to make sure that, do you mean "bandwidth" is Sigma. Because after applying the code above, it shows an error msg "The ratio of the time-bandwidth parameter to the symmetry parameter has exceeded 40 "
from fcwt.
I cannot completely recall how I did it back in 2021, but I guess I plotted the impulse response of both wavelets and compared them by sight. Matlab has written an article about this comparison on their site as well: https://www.mathworks.com/help/wavelet/ref/cwtfilterbank.html#mw_c07efe81-5d89-4243-85ba-51ec1ccfb2ff
Furthermore, I guess bandwidth is not actually the sigma used in the paper, but a variable that's proportionate to sigma (in other words, it uses a different scaling). Trial and error, and plotting should get you to your bandwidth value.
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Understood. Thanks a lot for the clarification. Furthermore, I have a few more confusion that I would also like to ask for your expert opinions,
Currently, I'm trying to build CNN-based eeg emotion recognition model with CWT, STFT, and fCWT respectively, and compare the performance of each model with different methods. However, I found that the performance of STFT is better than CWT (the parameters of both methods have been tuned to the highest performance on CNN). Therefore, would like to ask, if it is possible that using STFT on a narrow band frequency signal such as the Alpha band of an eeg signal will provide better performance than CWT ?
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I have opened a new issue for your new question about the performance of fCWT vs STFT. I will close this comment.
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Related Issues (20)
- I am not able to run the code in C++ HOT 1
- Linking problem: undefined reference to log@GLIBC_2.29 HOT 7
- installing the fCWT on python HOT 1
- Sample frequency limitation
- FR: Benchmarking against IRCAM "wavelet" Library
- libomp ubuntu build issues
- Installation issues on Apple M1
- Support for Custom Frequency Array Input HOT 1
- Wavelet coherence
- Template for `double`
- Dose it can be used for real-time application in processing low frequency signal?
- CMake function find_package() does not find fCWT-config.cmake configuration files HOT 1
- Generate fCWT for a short signal to be used as feature HOT 1
- Other mother wavelets HOT 1
- Continuous update for real-time application
- can't import FCWT and use it Google Colab python HOT 1
- Integration fCWT with Java
- fCWT on ARM Cortex M7 or so?
- memory error
- The CWT result???? c++
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