![matlab fft matlab fft](https://i.stack.imgur.com/TPKAZ.png)
I don’t know exactly how the Matlab fft works, but I believe that it internally pads the signal with zeroes to the next greatest power of 2, performs the fft, then spits out an answer without the padded zeros. In some cases, a 120 point FFT took LESS time than a 128 point FFT in some of my runs. I’ve done some quick runs using fft with N as a power of 2 and N not as a power of 2, and the speed difference was neglible. By using the next greatest power of 2, the fft command pads the original signal with zeros and proceeds to do a FFT on the signal. In my experience, there really isn’t a need to specify N as a power of 2. The Matlab documentation recommends that a power of 2 be used for optimal computation time. Power of 2The fft command within Matlab allows you to specify how many data points are in the transform. These two functions are very useful, and I still use them all the time! Set(positiveFFT, 'Position',)Īxis()Here’s what you should get:
#MATLAB FFT CODE#
Copy and paste the following code into the Matlab command prompt. %take only the first half of the spectrumįreq = freq(1:cutOff) Once again, let’s use the same sine wave and put it through this function.
![matlab fft matlab fft](https://i.stack.imgur.com/jeIDT.jpg)
X=fft(x)/N % normalize the data %only want the first half of the FFT, since it is redundant So let’s adjust out function above so that we only get the positive frequencies.Ī Custom Function for fft to Obtain only the Positive FrequenciesThe following function is a modification of the above function, and will help you plot only the positive frequencies of the spectrum. In general, the positive side of the spectrum is used, while the negative side is ignored. Thus, we only need one side of the spectrum. Redundant Information in the FFTAs you can see from the plots above, the information within the frequency spectrum is entirely symmetric. %remember to take the abs of YfreqDomain to get the magnitude!Īxis()Here’s what you should see:Īs you can see, this plot is basically identical to what we would expect! We get peaks at both -4 Hz and +4 Hz, and the amplitude of the peaks are 1.
![matlab fft matlab fft](https://cdn.educba.com/academy/wp-content/uploads/2020/07/Matlab-fft-6.jpg)
Now, copy and paste these commands into the Matlab command prompt. Let’s use the sine wave from above and do a quick example (Remember to set the Matlab directory to the location where you saved the previous m-file). It takes in as input the signal to be transformed, and the sampling rate.
![matlab fft matlab fft](https://i.ytimg.com/vi/k50JqKHLsn0/maxresdefault.jpg)
The function outputs the correct frequency range and the transformed signal. X=fftshift(X) %shifts the fft data so that it is centeredThis is a relatively simple function to use. %this part of the code generates that frequency axis if mod(N,2)=0įreq=k/T %the frequency axis %takes the fft of the signal, and adjusts the amplitude accordingly %this is a custom function that helps in plotting the two-sided spectrum %x is the signal that is to be transformed %Fs is the sampling rate Copy this code into an m-file and save it.
#MATLAB FFT HOW TO#
In addition, it will show you how to obtain a two-sided spectrum as well as a positive frequency spectrum for a given signal. The fft command only operates on the y-data (converting the y-data from the time domain into the frequency domain), so it’s up to the user to determine what the x-data in the frequency domain will be! This tutorial will show you how to define your x-axis so that your fft results are meaningful. When we represent a signal within matlab, we usually use two vectors, one for the x data, and one for the y data. The fft command is in itself pretty simple, but takes a little bit of getting used to in order to be used effectively. Introduction In this tutorial, we will discuss how to use the fft (Fast Fourier Transform) command within MATLAB.