Total energy in Time and Frequency Dimain
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I truly appreciated if somebody  can direct me how to measure total energy in a certain frequency band?
I have a signal and use this code to measure total enery and the result is reasonable.
E1_timedomain=sum(abs(x.^2))
but it measuers  total energy of whole signal. I just want to measure it  between [0-100] Hz. Appreciared!
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  Star Strider
      
      
 il 12 Dic 2020
        If you have R2018a or later, and the Signal Processing Toolbox, use the bandpass function to selectively filter the frequencies-of-interest.  Then do whatever calculations you want to do on the output.  If you have an earlier version, it is easy to design filters in MATLAB.  I will help you with that, if necessary.  
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Più risposte (3)
  Maria Amr
 il 14 Dic 2020
        1 Commento
  Star Strider
      
      
 il 14 Dic 2020
				You need to use an output: 
filtered_signal = bandpass(amp1,[1 78],fs);
  Maria Amr
 il 14 Dic 2020
        1 Commento
  Star Strider
      
      
 il 14 Dic 2020
				As always, my pleaure!  
(Also, in the future please post comments as Comments, not Answers.)  
  Paul
      
      
 il 10 Nov 2024
        
      Modificato: Paul
      
      
 il 10 Nov 2024
  
      Define a real-valued, finite duration signal of length N, assumed to be uniformly spaced samples collected as Fs = 2000 Hz
rng(100);
N = 1000;
x = randn(1,N); Fs = 2000; Ts = 1/Fs;
The total energy in this signal is computed in the time domain as
E = sum(abs(x).^2)
The total energy computed in the frequency domain is (taking advantage of the symmetry in the frequency domain because x is real-valued)
X = @(f) freqz(x,1,f,Fs);
E = 2*integral(@(f) abs(X(f)).^2,0,Fs/2)*Ts
Hence, the energy in the signal between 0-100 Hz is
E100 = 2*integral(@(f) abs(X(f)).^2,0,100)*Ts
Can also approximate E100 from the DFT samples.
Xdft = fft(x);
fdft = (0:N-1)/N*Fs;
E100 = 2*sum(abs(Xdft(fdft<=100)).^2)/N
Or better yet
E100 = 2*trapz(fdft(fdft<=100),abs(Xdft(fdft<=100)).^2)/Fs
Can also apply a very sharp, low pass filter to x and then compute the energy in the filter output as a rough approximation
y = lowpass(x,100,Fs,'Steepness',0.95);
sum(abs(y).^2)
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