USE fft(x) as a highpass filter

23 Ansichten (letzte 30 Tage)
fcarl
fcarl am 16 Jun. 2011
Kommentiert: Travis Morrison am 26 Jun. 2017
Hi,
I want to use the fft(x) function to create an highpass filter. I want to ask if the following procedure is correct:
1) take the signal x and make an fft(x).
2) Set frequencies up to 0.5 Hz to zero.
3) Make ifft(spectrum).
Is it right to set the first data points to zero or is there anything to pay attention to (e.g.: symmetry of the fft...). So if I set the first data points to zero, is this enough?
Thanks for your efforts!

Akzeptierte Antwort

Rick Rosson
Rick Rosson am 21 Jun. 2011
Here are some suggestions for improving the code.
I have inserted several new lines of code indented from the original code, and eliminated some lines of the original code by making them into comments:
signal=load(files{i});
dt = 0.008;
Fs = 1/dt;
N = size(signal,1);
dF = Fs/N;
f = (-Fs/2:dF:Fs/2-dF)';
% Band-Pass Filter:
BPF = ((lower_freq < abs(f)) & (abs(f) < upper_freq));
figure;
plot(f,BPF);
% time=0.008:0.008:size(signal,1)*0.008;
time = dt*(0:N-1)';
figure;
plot(time,signal);
% NFFT=2^nextpow2(size(signal,1));
signal=signal-mean(signal);
% spektrum = fft(signal,NFFT)/(size(signal,1));
spektrum = fftshift(fft(signal))/N;
figure;
subplot(2,1,1);
plot(f,abs(spektrum));
% spektrum(lower_freq:upper_freq,1)=0;
% spektrum(size(spektrum,1)- upper_freq+1:size(spektrum,1)-lower_freq+1,1)=0;
spektrum = BPF.*spektrum;
subplot(2,1,2);
plot(f,abs(spektrum));
% signal=ifft(spektrum); %inverse ifft
signal=ifft(ifftshift(spektrum)); %inverse ifft
HTH.
Rick
  4 Kommentare
syed aizaz
syed aizaz am 18 Dez. 2015
sallam sir... where is file i
Travis Morrison
Travis Morrison am 26 Jun. 2017
When converting back to real space you have to multiply by N. Other than that, thanks for the help!

Melden Sie sich an, um zu kommentieren.

Weitere Antworten (5)

Rick Rosson
Rick Rosson am 4 Aug. 2011
You are welcome. If you don't mind, could you please "Accept" the answer that helped resolve this issue?
Thanks!
Rick

Rick Rosson
Rick Rosson am 16 Jun. 2011
Before you can solve this problem, you need to know the sampling rate (in samples per second) of the signal x. Otherwise, you will not be able to figure out how many samples of the spectrum correspond to 0.5 hertz (the cut-off frequency).
For convenience, you may want to create the variable Fs to represent the sampling rate and Fc to repreesent the cut-off frequency. For example:
Fs = 200; % samples per second
Fc = 0.5; % hertz
Also, the spectrum returned by the fft function is double-sided. By default, it corresponds to the frequencies from 0 hertz up to Fs hertz. It will be easier to implement your filter if you swap the two halves of the spectrum, so that it will correspond to -Fs/2 up to +Fs/2. You can do so using the fftshift function:
X = fftshift(fft(x));
HTH.
Rick

David Young
David Young am 17 Jun. 2011
You might find this demo helpful.

fcarl
fcarl am 17 Jun. 2011
Hi Rick,
thanks for your answer. I want to show you the case in detail:
signal=load(files{i});
time=0.008:0.008:size(signal,1)*0.008;
NFFT=2^nextpow2(size(signal,1));
signal=signal-mean(signal);
spektrum = fft(signal,NFFT)/(size(signal,1));
spektrum(lower_freq:upper_freq,1)=0;
spektrum(size(spektrum,1)-upper_freq+1:size(spektrum,1)-lower_freq+1,1)=0;
signal=ifft(spektrum); %inverse ifft
In Lines 6 & 7 I try to eliminate special frequencies. I do this at the beginning of the spectrum and the end because of the symmetry. Is this right? upper_freq and lower_freq are the upper and lower bounds of frequencies i want to set to zero!
Thanks for your efforts! fcarl
  1 Kommentar
Jiahao Luo
Jiahao Luo am 18 Sep. 2015
I have the same issue now, did you make it work?

Melden Sie sich an, um zu kommentieren.


fcarl
fcarl am 22 Jun. 2011
Thanks very much! This helped me!

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by