Timeline for The derivative of a filter with respect to a output signal
Current License: CC BY-SA 4.0
20 events
| when toggle format | what | by | license | comment | |
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| Mar 17, 2020 at 12:09 | history | edited | Daniele Tampieri | CC BY-SA 4.0 |
Minor clarifications
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| Mar 17, 2020 at 11:20 | comment | added | Yongj Tang | @ Daniele, detailed explanation. I understand it, and really appreciate your kind help. | |
| Mar 17, 2020 at 10:58 | history | edited | Daniele Tampieri | CC BY-SA 4.0 |
typo removal
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| Mar 17, 2020 at 8:53 | comment | added | Daniele Tampieri | @YongjTang, I added a new note emphasized in bold in order to explain the meaning of $v$: in doing so, I hope to have dissipated a few of your doubts. However, despite not being able to answer immediately to your question, I am here. | |
| Mar 17, 2020 at 8:51 | history | edited | Daniele Tampieri | CC BY-SA 4.0 |
Added a note on the meaning of the variation $v(t)$.
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| Mar 16, 2020 at 8:30 | comment | added | Yongj Tang | @ Daniele, Thanks for your kind help, now I am confused with $v(t)$, it represents what? and how can I calculate it? | |
| Mar 16, 2020 at 8:24 | comment | added | Daniele Tampieri | @YongjTang For the other comments, I’ll answer later. | |
| Mar 16, 2020 at 8:20 | history | edited | Daniele Tampieri | CC BY-SA 4.0 |
edited body
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| Mar 16, 2020 at 8:20 | comment | added | Yongj Tang | @Daneile, I am confused with that you give $$ w(t)=\mathscr{F}^{-1}\left[\frac{\hat{p}(\omega)}{\hat{d}(\omega)}\right](t) $$ and $$ \frac{\mathrm{d}}{\mathrm{d}\varepsilon}{\mathfrak{w}[p+\varepsilon v]}_{\varepsilon=0} = \mathscr{F}^{-1}\left[\frac{\hat{p}(\omega)}{\hat{d}(\omega)}\right](t) $$ They are the same? Could you explain the last formular that how to get the derivative ? e.g. 1 calculate the FT with input data $d(t)$, 2 .... 3 inverse FT 4 convolute what? | |
| Mar 16, 2020 at 8:17 | comment | added | Daniele Tampieri | @YongjTang it’s a typo. I’ll correct it | |
| Mar 15, 2020 at 12:50 | vote | accept | Yongj Tang | ||
| Mar 15, 2020 at 12:50 | vote | accept | Yongj Tang | ||
| Mar 15, 2020 at 12:50 | |||||
| Mar 15, 2020 at 12:38 | comment | added | Daniele Tampieri | @YongjTang you’re welcome. And if you really like my answer, please consider accepting it. | |
| Mar 15, 2020 at 9:22 | comment | added | Yongj Tang | Daniele, Thank you very much for your kind help. I have read your answer carefully. Maybe I major not in math, and I am not familiar with some mathematical representations. I mainly want to implement it programmatically. I will try my best to read some you suggested and to understand it. Finally, I want to implement it with anumerical solution by using program language. If I have some confusion, I will ask you. Thank you very much. | |
| Mar 15, 2020 at 8:42 | comment | added | Daniele Tampieri | @YongjTang now the answer is fairly complete. However, feel free to ask for further explanation: probably I'll not answer to you immediately, but I'll do my best to help you. | |
| Mar 15, 2020 at 8:39 | history | edited | Daniele Tampieri | CC BY-SA 4.0 |
More explanations
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| Mar 15, 2020 at 7:37 | history | edited | Daniele Tampieri | CC BY-SA 4.0 |
Estensive revisions and explanations
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| Mar 15, 2020 at 7:30 | comment | added | Daniele Tampieri | @YongjTang I am posting a revision just now. Please wait a moment. | |
| Mar 15, 2020 at 7:29 | comment | added | Yongj Tang | Hi, Daniele, I add a small positive number to avoid the denominator of $\hat{d}(\omega)$ to be 0. Could you please explain what the $v(t)$ represents? If I want to calculate the derivative programmatically using the last formula, how to understand the $*$ in the last formula? or how can I do it? | |
| Mar 14, 2020 at 21:45 | history | answered | Daniele Tampieri | CC BY-SA 4.0 |