Timeline for Calculating derivative of experimental data (with noise) using tangent method
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 12, 2022 at 11:47 | comment | added | MarcoB | I recently found the ListD resource function that implements the fitting approach to calculating numerical derivatives. You may find it interesting as well. | |
| Oct 7, 2022 at 18:28 | comment | added | atapaka | @MarcoB I read another answer that actually implements S-G filter. But as soon as I saw that it is a convolution, I realised I would really need to study this in detail to understand its effect on data. Anyway, I tried it and Mathematica crashes immeditelly with it due to insufficient memory. Simply put, it cannot be used for this dataset in the version that is implemented in the post (linked in the question). | |
| Oct 7, 2022 at 14:15 | answer | added | MarcoB | timeline score: 0 | |
| Oct 7, 2022 at 13:50 | comment | added | MarcoB | "the process is somewhat a black box, especially the part when one filters the data" - depending on the field, some of those approaches are actually pretty standard (e.g. the Savitzky-Golay filter to smoothen spectroscopic data), whereas the one you mention does not sound as common to me. Perhaps you could familiarize yourself with those approaches first. | |
| Oct 7, 2022 at 3:41 | history | became hot network question | |||
| Oct 7, 2022 at 0:39 | answer | added | Michael E2 | timeline score: 4 | |
| Oct 6, 2022 at 21:30 | answer | added | Daniel Huber | timeline score: 3 | |
| Oct 6, 2022 at 19:37 | history | asked | atapaka | CC BY-SA 4.0 |