# How to find peak or dip separation in frequency domain signal

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Ozan Erturk 2020 年 5 月 15 日
コメント済み: Ozan Erturk 2021 年 3 月 31 日
Hello all,
I have a frequency domain signal I got from a network analyzer. The signal (attached) has repetetive dips that are separated by some frequency (in this case it's about 5.5MHz). I would like to see the frequency separation through the data so I started using "findpeaks" by inverting the data making dips into peak, which sort of works. If I apply the findpeaks approach to an analytic function it's perfect. But since the data measured is noisy, even though tweaking findpeaks properties like minimum separation and prominance etc. can fail from time to time.
I am wondering if there is a more elegant approach to this by simply treaating this signal like a time domain signal and take the FFT. I am not sure how to map the frequency data from the measured data and map it to freqeuncy of the fft signal.
Findpeaks approach: (you can just load S_data.mat and run the code)
%% FSR with FindPeaks Method
f=S(:,1);
sig=S(:,2);
figure(1);
plot(f,sig); hold on
sig_neg=-sig;
[Dips, indexes] = findpeaks(sig_neg,f,'MinPeakDistance',4.3e6,'MinPeakProminence',.01);
Dip_freq=indexes;
figure(1);plot(Dip_freq,-Dips,'ok');
FSR=diff(Dip_freq); %find and plot the separation of each dip within the freq range
figure;
plot(Dip_freq(1:length(Dip_freq)-1),FSR*1e-6,'-ob');
xlabel('Hz');ylabel('FSR in MHz');

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### 採用された回答

Sergio Yanez-Pagans 2021 年 3 月 28 日
These might work for you:
Hope you find this useful!
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Ozan Erturk 2021 年 3 月 31 日
I was using some derivative of this but your code is put together much more nicely ! Thanks!

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