I have a set of signals of varying lengths. I have provided an example of the same below -
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.
It appears that they all have the same waveform and length but vary in time of occurrence so some are missing part of the front and others missing part of the back compared to the mean. I used to be in comm electronics and what we might try is
Measure the time ticks of $t_0-t_1$ and $t_2-t_1$ where $t_0$ is the start, $t_1$ is the peak, and $t_2$ is the end of the mean. Then do the same measurements for the other waves (for the $visible$ portion) and identify the $greatest$ deviations among them to find the shortest time before the peak and the shortest time after. That done, subtract, delay, omit the portion of all waves, including the mean, that extend beyond the measured time intervals $t_1-t_b$ (beginning), and $t_e-t_1$ (ending). This should bring them all in phase for analysis of what they have in common. Let me know if I'm still not getting it..