How to find corresponding frequencies after viewing amplitude in descending order?

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?

Answer 1

[Mathieu NOE]

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

[Vikash Mahabir]

Thank you!!

[Mathieu NOE]

you're welcome !

[Vikash Mahabir]

https://www.mathworks.com/matlabcentral/answers/758109-signal-processing-finding-average-of-specific-values-only?s_tid=prof_contriblnk

Any insight with respect to this?

Answer 2

[dpb]

[DescendAmp,idx] = sort(peak_ft,'descend');
disp([peak_fr(idx) peak_ft])

Answer 3

[sugga singh]

thanks guys. was looking for it.