Identification of AR time‐series based on binary data

In this study, the authors consider the identification of auto‐regressive (AR) models for time‐series from one‐bit quantised observation sequences. The only available information is the fact that the samples of the time‐series are lower or higher than a threshold of quantisation. This threshold may be different from zero. An identification algorithm is presented and analysed. A recursive formulation is proposed, an extension for the identification of a non‐linear time‐series is also proposed.