Robust parameter estimation for periodic point process signals using circular statistics

We discuss the application of signal parameter estimators for periodic point process signals with missing data. The proposed estimation techniques operate on the observed event arrival time sequence of a pulse train signal and have application to pulse train signal classification and signal reconstruction. The methods we describe are based on the use of circular statistics and are shown to offer considerable robustness to a pulse train time series corrupted by missing pulses.