Identification of AR time‐series based on binary data

Abstract

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.