So, I have a huge number of amplitude modulated waves and I am attempting to determine which modulation parameter modulates each time series. To do this, I folded each time series over at the repetition frequency of the modulator wave, to produce an averaged modulation index for each time series.
Here is a (not particularly good, but convenient to produce) example. The left curve, if smoothed, produces a single preferred time point. The right produces two (a weak preference at 7, and a strong preference at 17). Technically the same is somewhat true of the one on the left but, for the sake of argument, lets ignore that for now.
I'd like to do something analogous to kernel density estimation for each time series, and then automatically determine the peaks from this shape. I know these aren't really distributions, but what I would like to do is automatically determine: A) the number of peaks per time series, B) the locations of these peaks. B sounds easy to me if I can do A. I suppose this means smoothing the curves and defining the local maxima via some sort of window, but thought some of you statistics experts might know of a proper method for this sort of thing.
Thanks in advance, Joseph