How to find corresponding frequencies after viewing amplitude in descending order?
6 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
Vikash Mahabir
am 26 Feb. 2021
Beantwortet: sugga singh
am 28 Feb. 2021
Good day. Below I have a piece of code written.
%% Peak detection Part
% In this part, we have defined a threshold value. So, all peaks above
% threshold value will be detected.
temp_fft = data_filt_ft;
% Normalize the FFT
temp_fft = temp_fft/max(temp_fft);
% threshold
th = 0.02; % i.e. 1% of maximum amplitude
temp_fft(temp_fft < th) = 0; %you can skip this step by commenting this.
% Plot FFT after thresholding
figure; plot(fr, temp_fft);
xlabel('Frequency(Hz)'); ylabel('Amplitude');
grid on;
% find peaks of the remaining data
[peak_ft, peak_loc] = findpeaks(temp_fft);
% frequency corresponding to peak
[peak_fr] = fr(peak_loc);
%Sort amplitude values into descending order
DescendAmp = sort(peak_ft,'descend');
% this fuction returns the fourier transform of the signal
function [ft, f] = fr_t(x, Fs)
L = length(x);
% NFFT = 2^nextpow2(L); % Next power of 2 from length of y
NFFT = L;
X = fft(x,NFFT)/NFFT;
f = Fs/2*linspace(0,1,floor(NFFT/2+1));
ft = abs(X(1:floor(NFFT/2+1)));
% ft = 20*log10(ft);
% plot(f,ft);
end
I am able to sort the amplitudes into descending order but I am unable to view the corresponding frequency values in that order. How can I view the corresponding frequency values in that order?
0 Kommentare
Akzeptierte Antwort
Mathieu NOE
am 26 Feb. 2021
hello
I modifed a bit your code and tested it with a two tone signal
see the line with peak_fr_sorted_values
clc
%% dummy data
Fs = 1e3;
samples = 1e4;
t = (0:samples-1)'*1/Fs;
signal = 0.7*cos(2*pi*50*t)+0.4*cos(2*pi*100*t)+0.1*randn(samples,1);
[data_filt_ft, fr] = fr_t(signal, Fs);
%% Peak detection Part
% In this part, we have defined a threshold value. So, all peaks above
% threshold value will be detected.
temp_fft = data_filt_ft;
% Normalize the FFT
temp_fft = temp_fft/max(temp_fft);
% threshold
th = 0.02; % i.e. 1% of maximum amplitude
temp_fft(temp_fft < th) = 0; %you can skip this step by commenting this.
% Plot FFT after thresholding
figure; plot(fr, temp_fft);
xlabel('Frequency(Hz)'); ylabel('Amplitude');
grid on;
% find peaks of the remaining data
[peak_ft, peak_loc] = findpeaks(temp_fft);
%Sort amplitude values into ascending order
[peak_ft_sorted_values,peak_ft_sorted_index] = sort(peak_ft,'ascend');
% frequency corresponding to peak
[peak_fr] = fr(peak_loc);
% and now sorted according to amplitude (above)
peak_fr_sorted_values = peak_fr(peak_ft_sorted_index)
% this fuction returns the fourier transform of the signal
function [ft, f] = fr_t(x, Fs)
L = length(x);
% NFFT = 2^nextpow2(L); % Next power of 2 from length of y
NFFT = L;
X = fft(x,NFFT)/NFFT;
f = Fs/2*linspace(0,1,floor(NFFT/2+1));
ft = abs(X(1:floor(NFFT/2+1)));
% ft = 20*log10(ft);
% plot(f,ft);
end
3 Kommentare
Weitere Antworten (2)
dpb
am 26 Feb. 2021
[DescendAmp,idx] = sort(peak_ft,'descend');
disp([peak_fr(idx) peak_ft])
0 Kommentare
Siehe auch
Kategorien
Mehr zu Parametric Spectral Estimation finden Sie in Help Center und File Exchange
Produkte
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!