Currently I did a FFT of a set of data which gives me a plot with frequency at x axis and amplitude at y axis. I would like to calculate the area under the graph to give me the energy.
I am not sure how to determinate the area because I am without the equation and also I only want a certain area of the plot rather than whole area under the plot. Is there a way I can do it?
A = integral (Fx, Xminimum, Xmaximum) will calculate the numeric integration of input function 'Fx', which in turn signifies the area under a curve. A = trapz (x, y) will also give the area under the curve represented by 'y'. Here 'x' is used to define the range or limits between which we want the area.
Y = fft( X ) computes the discrete Fourier transform (DFT) of X using a fast Fourier transform (FFT) algorithm. If X is a vector, then fft(X) returns the Fourier transform of the vector. If X is a matrix, then fft(X) treats the columns of X as vectors and returns the Fourier transform of each column.
Y = fftshift( X ) rearranges a Fourier transform X by shifting the zero-frequency component to the center of the array. If X is a vector, then fftshift swaps the left and right halves of X . If X is a matrix, then fftshift swaps the first quadrant of X with the third, and the second quadrant with the fourth.
The non-equidistant fast Fourier transform (NFFT) is an extension of the famous fast Fourier transform (FFT), which can be applied to non-equidistantly sampled data in time/space or frequency domain.
There are many ways to do numerical integration with Matlab. Here is an example:
%# create some data
x = linspace(0,pi/2,100); %# 100 equally spaced points between 0 and pi/2
y = sin(x);
%# integrate using trapz, which calculates the area in the trapezoid defined by
%# x(k),x(k+1),y(k),y(k+1) for k=1:length(x)
integral = trapz(x,y);
%# if you only want to integrate part of the data, do
partialIntegral = trapz(x(10:20),y(10:20));
%# show the integrated area
figure,
area(x,y);
hold on,
area(x(10:20),y(10:20),'FaceColor','red')
The FFT is discrete, not continuous - you just need to sum all the bin values. If you're looking at the power spectrum (magnitude squared) then the bin values are in W/Hz, so you would need to multiply each value (or alternatively just the sum), by the bin width in Hz to get power (and hence the total energy in your input sample).
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