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signal = np.cos(4 * np.pi * t) + (1 / 4) * np.cos(48 * np.pi * t) + (1 / 16) * np.cos(576 * np.pi * t)
the signals' frequencies are 2 Hz, 24 Hz, and 288 Hz).
after I use your codes svmdpy_torch.py t…
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During the decomposition process, for the first pair, Y(:,1) = X * wt1. As the iteration proceeds to the second pair, Y(:,2) = (X - Driving1) * wt2. So, why is it that after the final decomposition, Y…
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From reading the sklearn design decisions paper:
- Transformers
- motion correction
- with scoring function if we can find good metrics
- high pass filtering
- any other arbitrary fun…
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Here are 10 approaches to implement adaptive noise reduction, ordered by complexity/effectiveness:
### 1. Enhanced Spectral Subtraction
- Track noise floor during silence periods
- Use overlappin…
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Nearest neighbors and DelayEmbeddings are too advanced dependencies for this repo (probably)
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got prompt
K:\AIGC\dapao_ComfyUI\ComfyUI\models\clip\siglip-so400m-patch14-384
Loading VLM's custom vision model
Requested to load SiglipVisionTransformer
Loading 1 new model
loaded completely 0.…
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Dear author,
Could you please tell me which model F-Block uses?
Thank you very much.
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# Adding a Decomposition Class
I am currently in the process of planning some simplification in pyxem and it seems like there is a missing Class for dealing with decomposition/ vectorized data repres…
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When I use the pywt.swt function for a level 1 transform I get different results than when doing a manual convolution with the low pass and high pass filters using wavelet.dec_lo and wavelet.dec_hi. I…
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### Benefits to the change
This would allow users to use Nilearn with ICA-AROMA or tedana confounds. In `nilearn.interfaces.fmriprep.load_confounds`, users could use AROMA regressors without havi…
tsalo updated
1 month ago