Timeline for Fourier vs Laplace transforms
Current License: CC BY-SA 2.5
8 events
| when toggle format | what | by | license | comment | |
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| Nov 27, 2010 at 0:42 | comment | added | Jon Yard | Not sure I saw this explicitly mentioned here, but it could be that the Fourier transform doesn't exist but the Laplace transform does, only on a subset of the complex plane (the so-called "region of convergence", or ROC). When the ROC contains the imaginary axis then you get back the Fourier transform by evaluating there. | |
| Nov 26, 2010 at 20:46 | comment | added | timur | $t<0$ is future? | |
| Feb 25, 2010 at 20:15 | comment | added | Anweshi | Again a practical suggestion, seeing below that you use RC filters: I have no idea how neurons are modelled. But, say, if you want to do control engineering, do Laplace transforms, and if you want to do signal analysis, processing, etc., then use Fourier transforms. If both looks usable, use Laplace, because Laplace is somewhat simpler. | |
| Feb 24, 2010 at 19:28 | history | edited | Anweshi | CC BY-SA 2.5 |
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| Feb 24, 2010 at 19:14 | comment | added | Anweshi | @Qiaochu: There is little difference between two-variable Laplace transform and the Fourier transform. Each can be got from the other looking at the imaginary axis. | |
| Feb 24, 2010 at 19:13 | history | edited | Anweshi | CC BY-SA 2.5 |
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| Feb 24, 2010 at 19:05 | comment | added | Qiaochu Yuan | If you wanted to take an integral over R, you could still just use the two-sided Laplace transform instead of the Fourier transform. | |
| Feb 24, 2010 at 19:03 | history | answered | Anweshi | CC BY-SA 2.5 |