Fft time axis for a signal that is a function of frequency

In summary, an FFT of a sampled time signal yields different results depending on what domain it is in.
  • #1
wattacatta
2
0
Hello!
I am attempting to do an FFT on a signal e^(jω+nδω)t, where t is constant and for n=0:N-1. This signal starts off at ω when n =0 and then increments in steps of δω until it reaches the final frequency ω+(N-1)δω.

Performing an FFT on this signal will put me in the time domain so my x-axis is time. I have been told that the waveform will have a total duration of T = 1/Δω and Δt will be 1/(N*Δω). I asked my instructor why that is the case and he told me that it is all the same as if I were working in the time domain, the FFT works the same whether I am working with time, frequency, or apples. However, I cannot see this. I have been searching online to try to find an explanation but all I can find is on going from time to frequency, not from frequency back to time.
The closest thing I found on physics forums:
https://www.physicsforums.com/showthread.php?t=236201

however, I can't post an entry to that thread. Also that thread confirms that T = 1/Δf and Δt = T/N = 1/(N*Δf), but doesn't really provide an explanation.

The way I see it, we get different results depending on what domain we are in:
When doing an FFT of a sampled time signal, you have a sampling frequency (fs) from which you can calculate the Sample Period(Ts) by just taking the inverse. We also know that in the frequency domain we will have frequency components in the range -fs/2 to fs/2.
But if you have a signal that we are essentially sampling in the frequency domain for a particular instant of time, "fs" is now possibly our Δω, so to get Ts, we can do 1/fs. But, this does not calculate Ts, rather it is Ttotal_observation_time (which in the time domain would be calculated as Ttot = (N-1)*Δt). I would jump for joy if the correct answer were that Δt = 1/Δf but it is not so, rather this is equal to the overall duration of the time domain signal.

So my confusion is that somehow, 1/fs yields the total observation time in the frequency domain, whereas in the time domain, it yields the sample period; Thus I think it does matter what domain I am in. Please someone help me see otherwise!If there is someone who can understand what I cannot see please provide me with some help that might make me understand. Thank you in advance!
 
Engineering news on Phys.org
  • #2
Furthermore, the range in the time domain is now 0 to 1/Δf, which does not parallell the -fs/2 to fs/2 range in frequency in any way.
 

1. What is the FFT time axis for a signal that is a function of frequency?

The FFT (Fast Fourier Transform) time axis for a signal that is a function of frequency represents the time domain of a signal that has been transformed from the frequency domain using the FFT algorithm. It shows the relationship between time and frequency components of the signal.

2. How is the FFT time axis calculated?

The FFT time axis is calculated by dividing the total number of samples in the signal by the sampling rate. This gives the time interval between each sample point on the time axis.

3. Can the FFT time axis be adjusted?

Yes, the FFT time axis can be adjusted by changing the sampling rate or the number of samples in the signal. This will affect the resolution and accuracy of the time domain representation of the signal.

4. Why is the FFT time axis important?

The FFT time axis is important because it allows us to analyze and interpret the time-domain characteristics of a signal that has been transformed from the frequency domain. It helps us understand the relationship between time and frequency components of the signal and can reveal important information about the signal's behavior.

5. Are there any limitations to the FFT time axis?

There are some limitations to the FFT time axis, such as the trade-off between frequency and time resolution. Increasing the number of samples in the signal will improve the frequency resolution but decrease the time resolution, and vice versa. Additionally, the FFT assumes that the signal is periodic, so it may not accurately represent non-periodic signals.

Similar threads

  • Electrical Engineering
Replies
4
Views
817
  • Electrical Engineering
Replies
3
Views
47
  • Electrical Engineering
Replies
6
Views
930
  • Electrical Engineering
Replies
20
Views
2K
Replies
6
Views
971
Replies
18
Views
2K
Replies
4
Views
2K
  • Electrical Engineering
Replies
11
Views
1K
Replies
68
Views
3K
Replies
7
Views
3K
Back
Top