如何找到向量的相对最小值（不是最小值）

Question

Let's suposse I have a vector of values whose representation is the following one:

The vector of data has 2000 elements and as you see, there is another vector with degrees between -180º and 180º. I'd like to find the indices of each minimum peak, but I don't know how to implement the algorithm.

In other cases, I set a threshold value (for example -75dBm) and considered a minimum any value under -75dBm, but in this case, there are peaks above -70dBm and I can't increase the threshold value since my measurements will be wrong.

I hope someone can help me. Thank you for your responses.

Answer 1

For data like this, your best bet is to smooth it and then use findpeaks.

For an example

%% parameters to adjsut
%smoothing window length
smthwin=50;
%minimum peak prominence
mpp=0.01;

%% create some test data
x=(1:1000)/1000;
y=sin(3*x-0.5).*sin(5*x).*sin(9*x-0.1).*sin(15*x-0.3)+rand(size(x))/10;

%% smooth and findpeaks
%smooth it
%here I use a median filter, but smooth() is a great function too with lots of options 
ysmth=medfilt1(y,smthwin);

%use findpeaks on -y to find local minima
[pks,pks_loc]=findpeaks(-ysmth,'MinPeakProminence',mpp);
%the location of the local minima is 
mins=x(pks_loc);

%%plot to check
figure
plot(x,y)
hold on
plot(mins,-pks,'o','LineWidth',2)