  A short sample sequence of a finite-length pulse signal allows for its
reconstruction only if the signal has a sparse representation in some basis.
The recurrence of the pulse allows for a statistical approach to its
reconstruction. We propose a novel method for this task. It is based on the
distribution of short sample sequences treated as points which lie along a
curve in a low-dimensional Euclidean space. We prove that the probability
distribution of the points along this curve determines the underlying pulse
signal uniquely. Based on this discovery, we propose an algorithm for pulse
estimation from a finite number of short sequences of pulse-stream samples.
