Excellent video, a practical introduction to how to use FFT to find the peak frequency in a noisy signal. You can take this a step further and find the n peak frequencies in a signal and attempt to reconstruct the original signal. Thank you!
great video man, you explained everything so well not only that those small boxes at top right corner telling what the function does is a really smart idea. for the first time I understood everything in a programming tutorial, thank you brother : )
Thanks for the great video! One question, 9:40 why sample freq goes symmetric around zero, why not go with one side of the x axis [0 .... n ] ? so mathematically, what are these generated frequencies? are they unique?
The range of the Discrete Fourier Transform is -infinity to positive infinity to include all possible discrete signals. It is common practice to truncate spectrum from 0 Hz to Fmax (defined by sample rate, max resolution of sensor accuracy etc.)
Great tutorial! I think it-s recommended to build graph of each intermediate output in JPEG format, for better understanding. So that the student had some pyplot practice.
Cool video, sir. Great explanation! But can you plot the bunch of numerical stuff instead of just print it? I think it'll be more intuitive for the viewers
Thanks a lot for this video. As someone with no engineering background, this demonstration makes the concept much easier to understand.
Thanks
Excellent video, a practical introduction to how to use FFT to find the peak frequency in a noisy signal. You can take this a step further and find the n peak frequencies in a signal and attempt to reconstruct the original signal. Thank you!
great video man, you explained everything so well not only that those small boxes at top right corner telling what the function does is a really smart idea. for the first time I understood everything in a programming tutorial, thank you brother : )
Excellent video. keep it going, you helped me a lot on my mechanical dynamics class.
Thanks bro.
Thanks for the great video! One question, 9:40 why sample freq goes symmetric around zero, why not go with one side of the x axis [0 .... n ] ? so mathematically, what are these generated frequencies? are they unique?
The range of the Discrete Fourier Transform is -infinity to positive infinity to include all possible discrete signals. It is common practice to truncate spectrum from 0 Hz to Fmax (defined by sample rate, max resolution of sensor accuracy etc.)
Great tutorial! I think it-s recommended to build graph of each intermediate output in JPEG format, for better understanding. So that the student had some pyplot practice.
Great suggestion!
Thank you, it's very clear explanation
Thank you so much, it helped a lot in understanding FFT
You're welcome sir
Thank you very much. Your video is very clear and functional.
A pretty easy tool for filtering, nice intro!
Thank you so much. It's very useful and your explain clearly.
what arguments did you use to plot the amplitude vs frequency graph
Nice explanation and tutorial; it helped me understand FFT a bit better.
Excellent video for a starter like me, thanks
Thanks man, very good video. Very simple from the information i looked online
Very helpful, perhaps can add more plotting when showing how the data is like.
Amazing video I like it
am getting both amplitude position and peak frequency 0, what should i do i am not getting valid result
Cool video, sir. Great explanation! But can you plot the bunch of numerical stuff instead of just print it? I think it'll be more intuitive for the viewers
thanks for watching, such a great suggestion!
thanks for the video, just don't understand how the amplitude could be 100 in the spectrum when it's supposed to expect be 1
Thanks. This helped a lot!
Is it posible to generate a "clean" file out of fft?
would have understood better with graphical representations
Nice
Please code seen clear or share PDF link .
Where is the magnitude sir?
The argument of sin should be omega*t, not 2*pi*t( i see now you divided by the period)
noob