This corresponds to time(s) tB(bIndices(:)). So you have two time vectors: tA and tB, and a vector of time indices bIndices that contains the known peak(s). If an exact solution isn't possible, even an approximation would be great help. This is why I need a way of aligning the time vectors/series and thus the data. Those times are the only times of interest to me in data set A. It comes down to the fact that I need to look at data set B, and find the times that correspond to peaks in the data. Data-set B and its time vector have a length of 828 (828x1 double). For data-set A, the data and the time vectors have a length of 25042 (25042x1 double). My problem here is aligning the time for the different types of data collected. However, the instrument for data-set B is averaging the data and only records a point once every minute or so. For example, the measurements for data-set A are recorded every 100 ms. The format of the data should all match, but the time the data points were recorded for each set aren't necessarily aligned (they each have their own time vectors). All of the times are given in fractional day. Let's say we have data-set A and data-set B (the experiment itself doesnt matter). I should preface this by saying that I dont really program much so sorry if this is a dumb question and seems like a waste of time. So my friend and I ran an experiment 2 weeks ago and we've encountered something a bit weird.
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