I have several signals that consist of repetitive units. In the figure you'll clearly see the variability of the signals, that increases top down. The first signal is super repetitive and units are indicated with green lines. In the third, you'll see peaks and in the middle a little insertion that I know consists of rather diverging units, which still are units however (red lines). The remaining three signals display the variation more.
Which signal processing / machine learning tool should I use in order to detect these units? With thresholding it works to find the significant peaks, but once signals get funky it's really difficult to accurately detect unit positions.
I made some progress with spectral analysis and plotted a filtered signal over the initial signals. Indicated by the blue arrow is a region variable repeats. Here, the amplitude of the original and filtered signal do not match. Same for the red arrow. Similar effects for signal further down.