Timeline for How to realize a Fourier Transform on a non-uniform sampling data
Current License: CC BY-SA 3.0
13 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Mar 17, 2016 at 22:40 | history | edited | Daniel Lichtblau | CC BY-SA 3.0 | added 224 characters in body |
| Mar 17, 2016 at 17:19 | history | edited | Daniel Lichtblau | CC BY-SA 3.0 | added 1910 characters in body |
| Mar 17, 2016 at 6:51 | comment | added | user14634 | @BlacKow, Yes, Interpolation did something weird with the data, but the Interpolated data is highly consistent with the original data, except these weird points. The small portion of weird points almost doesnot effect the final result, because the shape of the peaks obtained from these two methods are almost the same. So, I think your method is also good. | |
| Mar 17, 2016 at 6:32 | comment | added | user14634 | @BlacKow, Thanks a lot for your good comments. Yes, the main peak should be around 0.2 and the unit is 1/fs, or 10^15 Hz. I think this result is reasonable with my experiment. | |
| Mar 17, 2016 at 6:23 | vote | accept | user14634 | ||
| Mar 17, 2016 at 6:23 | comment | added | user14634 | @Daniel Lichtblau, If we enlarge your first figure, we can see a [email protected]. 1.3/(2 Pi) = 0.207. This is consistent with the peak position calculated by BlacKow. Further, after a careful check, I find the figure shape is also basically the same as the peak by BlacKow. So, we can obtain the same result by using these two different methods. My problem was solved. Again, many thanks to Daniel Lichtblau and BlacKow! | |
| Mar 16, 2016 at 17:48 | comment | added | BlacKow | @user14634 Generally speaking I like this solution better, you are right Interpolation did something weird with your data. You have to figure out the X scaling. I'm pretty sure that the main peak should be around 0.2 because the period of your oscillation is about 5 (see Fig.2). It is a problem of simple scaling. I don;t have access to MMA right now so I can't help with that immediately. | |
| Mar 16, 2016 at 14:56 | comment | added | Daniel Lichtblau | One difference is I did not use a factor of 2*Pi in the exponent. When that goes in, the spike moves to the vicinity of 7.5. The method of @BlacKow has spikes at around .2 and 7.2. Which might be coincidence, I don't know. | |
| Mar 16, 2016 at 8:41 | comment | added | user14634 | @Daniel Lichtblau, Thank you so much for this good answer. I hope to know the reason for the different results calculated by these two methods. | |
| Mar 15, 2016 at 23:04 | comment | added | Daniel Lichtblau | @BlackKow Afraid I don't have an answer for either question. Well, there may be a peak at .2, I guess I should zero in so to speak to find out what is happening at small frequency values. | |
| Mar 15, 2016 at 22:31 | comment | added | BlacKow | Now I wonder why your answer is different from mine... And I kinda like yours better, interpolation messed up data? | |
| Mar 15, 2016 at 22:28 | comment | added | BlacKow | How is your frequency axis scaled? If you look at Fig. 2, your main peak should be around 0.2, right? | |
| Mar 15, 2016 at 22:08 | history | answered | Daniel Lichtblau | CC BY-SA 3.0 |