IEEE Transactions on Signal Processing

Assume that we observe a large number of signals, all of them with identical, although unknown, shape, but with a different random shift.The objective is to estimate the individual time shifts and their distribution.Such an objective appears in several biological applications like neuroscience or ECG signal processing, in which the estimation of the distribution of the elapsed time between repetitive pulses with a possibly low signal-noise ratio, and without a knowledge of the pulse shape is of interest.We suggest an M-estimator leading to a three-stage algorithm: we first split our data set in blocks, then the shift estimation in each block is done by minimizing a cost function based on the periodogram; the…