Timeline for Help me understand the stages involved in filtering a signal using Discrete Fourier Transform
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Apr 4, 2019 at 18:11 | vote | accept | Duck | ||
| Mar 12, 2019 at 6:55 | comment | added | robert bristow-johnson | the kind of filtering that you doing is linear convolution. and the kind of filtering that multiplying the DFT result is doing is circular convolution. now there are two methods of forcing the DFT (that knows how to do circular convolution) into doing linear convolution. they are Overlap-add and Overlap-Save. you are doing Overlap-Save with the buffer size of 1 sample and an FIR length having the same length of the DFT. because that is 256 samples, you can independently control the magnitude and phase of 63 frequencies and the magnitude (and not phase) of DC and Nyquist component. | |
| Mar 12, 2019 at 4:51 | answer | added | Dan Szabo | timeline score: 1 | |
| Mar 11, 2019 at 20:47 | comment | added | Duck | This is real time. I let the sensor capturing data for 10 seconds. In 10 seconds I will have 256 readings. When the program hits 256 samples, I analyze it. Next sample will be added to the end of that array and the first one will be dropped. Every operation like DFT and so, are over this array of 256 samples. | |
| Mar 11, 2019 at 20:05 | comment | added | robert bristow-johnson | Is this a single buffer of data that you are filtering? Or is it a stream of data that you are filtering in frames? | |
| Mar 11, 2019 at 19:38 | history | asked | Duck | CC BY-SA 4.0 |