Can we extract amplitude of levels in a signal using "findchangepts" function?
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ishita agrawal
el 11 de Mayo de 2017
Comentada: Christopher Young
el 28 de Sept. de 2017
Hi, I want to find points of abrupt changes in my data signal to obtain various levels in the signal. I am using 'findchangepts' function. I am able to find correct indexes of change points. I also want to retrieve amplitude of each level. For reference, I have attached image of one of my signals operated with 'findchangepts' function. I want to find values of levels shown in "red color".
I am new to MATLAB. Also, can suggest any other method to find changes in signal (my data contains very sharp changes for small duration, appear like sharp peaks in XRD)?
findchangepts(x, 'Statistic', 'mean', 'Threshold', 0.2);
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Star Strider
el 11 de Mayo de 2017
You have to calculate the interval means yourself. That can be done in a loop.
The Code —
t = 0:50; % Create Data
x = 50 + sin(2*pi*t/40) + cos(2*pi*t*10/50)*0.1; % Create Data
figure(1)
plot(t, x);
grid
ipt = findchangepts(x, 'Statistic', 'mean', 'MinThreshold', 0.2); % Get Change Point Indices
intvls = [1 ipt length(t)]; % Define Intervals
for k1 = 1:length(intvls)-2
interval_means(k1) = mean(x(intvls(k1):intvls(k1+1)-1)); % Calculate Means For Each Interval
end
interval_means(k1+1) = mean(x(intvls(k1):intvls(end))); % Calculate Means For Last Interval
figure(2)
findchangepts(x, 'Statistic', 'mean', 'MinThreshold', 0.2); % Plot Change Points
In order to avoid overlaps in the change point indices (so the value at the same index is not included in successive intervals), the end-points of each interval are not included in the interval. It is necessary to calculate the last interval separately so it does include the value of the end of the last interval.
This should do what you want.
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Christopher Young
el 28 de Sept. de 2017
There appears to be a minor error in the last line of this code snippet. The starting index for x should be k1+1 not k1.
interval_means(k1+1) = mean(x(intvls(k1):intvls(end)));
should read as,
interval_means(k1+1) = mean(x(intvls(k1+1):intvls(end)));
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