FFT analysis of multiple signals with the same response length

Question

Denis Bobylev 2020-1-23

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/501618-fft-analysis-of-multiple-signals-with-the-same-response-length

评论： Star Strider 2020-1-26

I have a dataset of the responses of a dynamic system in a time- domain. The signal is 1 second long and sampling frequency is 2000 Hz. I have 100 of different system configurations, meaning that my dataset has the shape of 2000x101, where the column 1 represents time and the rest columns are reponses of the system. How to perform FFT analysis for each signal and save obtained signals in frequency- domain to the new dataset? By this moment I can perform FFT only for 1 signal, the code is below. Obviously, for loop is need for this operation, but I don't have much experience to implement it for this problem.

%load data
Data = Data4FFT(:,2);
Time1= Data4FFT(:,1);
L = numel(Data);                                                   
Fs = 2000;                                                        
Fn = Fs/2;                                                      
Ts = 1/Fs;                                                      
t = linspace(0, L, L)*Ts;                                       
                                                
FTS = fft(Data)/L;                                                 
FvHz = linspace(0, 1, fix(L/2)+1)*Fn;                           
Iv = 1:numel(Fvrs);                                             
figure(2)
plot(FvHz, abs(FTS(Iv))*2)
grid
xlabel('Frequency (Hz)')
ylabel('Amplitude')
title('Response in Frequency Domain')

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Answer 1

Star Strider 2020-1-23

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/501618-fft-analysis-of-multiple-signals-with-the-same-response-length#answer_411633

在 MATLAB Online 中打开

The fft function operates column-wise (unless the argument is a vector or you tell it otherwise), so this is all that is necessary:

Data4FFT = [((0:1999).'*5E-4), rand(2000,100)];             % Create Matrix
L = size(Data4FFT,1);                                       % Signal Length
t = Data4FFT(:,1);                                          % ‘... first column is time ...’
Data = Data4FFT(:,2:end);
Fs = 2000;                                                        
Fn = Fs/2;
Ts = 1/Fs;
FTS = fft(Data - mean(Data))/L;                             % Subtract Mean To Eliminate D-C Offset
FvHz = linspace(0, 1, fix(L/2)+1)*Fn;
Iv = 1:numel(FvHz);
figure(2)
plot(FvHz, abs(FTS(Iv))*2)
grid
xlabel('Frequency (Hz)')
ylabel('Amplitude')
title('Response in Frequency Domain')