1
$\begingroup$

I observed than people often compute the DFT of a signal using FFT and just observe the peaks in the "modulus VS frequency" diagram (kind of a power spectrum density). Obviously only half of the information appears in this diagram and it is not possible to retrieve the original discrete signal from this plot only.

Question: In practice, in which cases is the "phase VS frequency" plot needed or not?

|improve this question
$\endgroup$
  • $\begingroup$ Is your question only about plots? FFT phase results are required when using an FFT for filtering, such as in overlap-add/save fast convolution. Phase results are also required by algorithms that measure the phase difference between offset DFT windows, such as for phase vocoder analysis/resynthesis algorithms. Etc. $\endgroup$ – hotpaw2 Sep 19 '16 at 22:04
  • $\begingroup$ @hotpaw2 Well, not specifically plots, just phase in general. I have never seen people using FFT phase in mechanics, for example - this is probably because resonance phenomena, which are of intersest, appear in terms of modulus. The examples you give are exactly what I am looking for. E.g. to lowpass a signal, you cannot just cut the frequencies about a given threshold in the amplitude-freq. diagram, because of the phase, as you write. But I am not very comfortable with this... $\endgroup$ – anderstood Sep 19 '16 at 23:44
  • $\begingroup$ In mechanics, phase vs. frequency can be very important in control systems, the difference between stable and unstable feedback (steam engine speed governors, etc) $\endgroup$ – hotpaw2 Sep 20 '16 at 1:11
  • $\begingroup$ phase is part of the mathematics of the DFT. sometimes we don't care about it, but often when phase is totally overlooked, something bad or undesireable happens. usually when drawing the result of the DFT, phase is ignored. but just in the sketching of the DFT output. $\endgroup$ – robert bristow-johnson Sep 20 '16 at 3:00
1
$\begingroup$

From the perspective of filtering, a common LTI system will weight each components in the input signal: (1) weighting means changing the magnitude values (it is apparent in multiplication of two complex numbers), thus it is often to observe the magnitudes (this does not mean the phase is not important; (2) of course, phase information is also part of the whole signal, and although the phase information may be also changed, but the phase is not apparent; (3) we can consider a FIR filter, and compare the changes of both magnitude and phase.

|improve this answer
$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.