Their lengths vary between 186 to 202, with a mean length of 197. I am looking to rescale them to the mean length. I am looking for ideas to do the same. Perhaps a good start will be reinterpolation, but I am open to other approaches too.
If you really want to scale data, you can look at the scale transform, detailed in The scale representation, L. Cohen, 1993. There also exists a time-scaling method given in A. Papoulis, "Signal Analysis", McGraw-Hill, p. 290, 1977; one Matlab/Scilab/Octave implementation is provided in the DiscreteTFDs toolbox by Jeffrey C. O'Neill.For the latter, you just have to provide a scaling factor proportional to the inverse of the signal's length.
However, in the same line as @Florian, and looking at the signals, I would be more prone to 1) find the maxima at fractional steps through interpolation (eg Quadratic Interpolation of Spectral Peaks) 2) realign with fractional filters (Splitting the unit delay: tools for fractional filter design) 3) truncate signals.