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| author | Christian Kolset <ckolset@colostate.edu> | 2025-10-17 13:20:11 -0600 |
|---|---|---|
| committer | Christian Kolset <ckolset@colostate.edu> | 2025-10-17 13:20:11 -0600 |
| commit | 06b8d5d198eec25d6ca6d40368bb7b9591aa0e5d (patch) | |
| tree | dd8a74ff352053183366975a02dab81d4e6d64eb /admin | |
| parent | 4a3400f5ba347afa9743a4424c0ea841c799b2cf (diff) | |
vault backup: tabS7 2025-10-17 13:20:11
Diffstat (limited to 'admin')
| -rw-r--r-- | admin/meeting-notes/2025-10-13.md | 5 |
1 files changed, 4 insertions, 1 deletions
diff --git a/admin/meeting-notes/2025-10-13.md b/admin/meeting-notes/2025-10-13.md index 93f22d2..a191670 100644 --- a/admin/meeting-notes/2025-10-13.md +++ b/admin/meeting-notes/2025-10-13.md @@ -29,4 +29,7 @@ Module 4: Data Analysis and Processing - 4.5. Data Cleaning (linear regression, least square fitting, extrapolation, moving average) -> One Lecture - 4.6. Data Filtering & Signal Processing (filters: Gaussian Filter, Sobel edge detection, Kalman, Butterworth, FFT) -> We need to give a lecture of what is/how it works Digital filter design (lowpass, highpass, bandpass, filter response curves, how does one select a given filter). One lecture all theory so that in the second lecture they learn how to select different filters. -> Two lectures - 4.7 Image processing: apply some of the filtering to make images sharper/crispier, teach them how to make videos/gifs out of images. -> One Lecture. Possible application: **_from CFD density data obtain Synthetic Schlieren images (Ciprian will send you this!)_** -
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