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I have 2 different digital plots on an X-Y Graph. They consist of 2 differently sampled datasets, each with its own timestamp that are plotted on the same graph. What I want to do is find a fast way to search the entire time range to see if there is ever an instance where each of the 2 signals are ever simultaneously "1". If I search and compare the data arrays themselves, each array would require an interpolation between elements so that I could line them up.
Is there a benefit like converting these two to waveforms to find this sweet spot where both waves = 1?
I wonder how hard it would be to re-create new arrays with the same data, only higher time precision. Then you can go through and compare them at a smaller scale.
If this data was analog data instead of boolean data, I was thinking perhaps doing a curve fitting for each and then solving for a set of equations using Matrix Algebra, but I'm not sure if that is possible with the data you have. Maybe others have ideas on how to do this with your data?
