Trouble understanding fft norm axis sampling frequency etc

AI Thread Summary
Understanding the Fast Fourier Transform (FFT) requires clarity on the normalized frequency axis and its relation to sampling frequency. The user is confused about extracting real frequency values without knowing the sampling frequency, referred to as the "magicNumber." They provided examples using numpy to illustrate their point, noting spikes in the frequency domain but struggling with multiple frequency components. The discussion suggests that practical experimentation with known signals can aid comprehension of FFT properties. Engaging with examples and visualizing results is recommended for better understanding.
eric hardin
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Hello,
I have a question regarding fft's. My experience with working with Fourier transforms is pretty much limited to transforming contrived functions pen and paper style. But now I need something and I think the fft is the appropriate tool, but I'm having a hard time understanding some aspects of it. I figured you EE guys would be the best to ask... please be gentle.
I'm using numpy, I think it's a lot like matlab, please forgive if it's not.
My question deals with reading the normalized frequency axis. I think I understand that you can directly read the frequency and that the frequency is in units of samples per cycle. But I feel like I'm missing something to pull out the real frequency if I don't know the sampling frequency.
So, of course, I started out with simple examples (a week ago) like the sinusoid according to some tutorials:
n=arange(0,30,1)
magicNumber = 10
x=cos(2*pi*n/magicNumber)
N1=2**8
X1 = abs(fft(x,N1))
F1 = linspace(0,N1-1,N1)/N1
pylab.plot(F1,X1)
And I see a spike at 0.1 and 0.9 corresponding to the frequencies 1 and -1. But what I don't understand is how to pull out that frequency if you don't know what I called the magicNumber, which is the sampling frequency, correct? Also what if the signal looks like,
x=cos(2*pi*n/2)+cos(2*pi*n/10).
Those are different sampling frequencies, so to which does the normalized frequency axis correspond.
Sorry if this is an elementary question, but I feel like I've looked around enough to warrant asking people.
As always, because I don't understand the material, I probably gave the wrong details. Please let me know if information is required.
My eternal gratitude,
Eric Hardin
 
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I saw that some people had a look at this thread. Nobody's responding though. Is it because it's a stupid question or because nobody understands what I'm trying to get at? If you see this and you don't know the answer or what I'm talking about, could you just write something like why you don't know. It might help me get to the answer.
Thanks
 
eric hardin said:
I saw that some people had a look at this thread. Nobody's responding though. Is it because it's a stupid question or because nobody understands what I'm trying to get at? If you see this and you don't know the answer or what I'm talking about, could you just write something like why you don't know. It might help me get to the answer.
Thanks

Hahaha, I think it's a mixture of both. Usually when you think too much about a (relatively) well known concept, the solution is to simply work out an example and try to understand what's going on. In matlab, for example, plot a sine wave which you know the properties of. You can take the fft of it, play around with the graph and try to evaluate every value you see; it's there for a reason.
 
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