How to filter data that detects peaks or irregularities?
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I am trying to build a code that detects these peaks. This graph represents the change in position in time. What I am doing is read the distance timestep by timestep.
I compare the new distance minus the old distance, if this values difference is higher than 5 meters I assume theres a peak. The problem is that each dataset have undefined number of peaks and undefined number of green datasets to save.
How can I solve this?
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Answers (1)
Star Strider
on 18 Jan 2020
Several functions already exist to do that, among which are findpeaks, islocalmax, ischange, and others.
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Image Analyst
on 18 Jan 2020
Mariana, make it easy for people to help you, not hard. Attach your data in a .mat file with the paper clip icon after you read this link.
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