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Conference Papers Year : 2018

Estimation of Auto-Regressive models for time series using Binary or Quantized Data

Abstract

In this paper, we first present an algorithm for the estimation of an Auto-Regressive model of time series using output data of a binary sensor. This algorithm is based on the estimation of the autocorrelation of time series for a threshold different from zero. The algorithm is then extended to time series with several quantization levels. Simulation results are given to show the effectiveness of the proposed approaches.

Dates and versions

hal-01826047 , version 1 (28-06-2018)

Identifiers

Cite

Romain Auber, Mathieu Pouliquen, Eric Pigeon, Mohammed M'Saad, Olivier Gehan, et al.. Estimation of Auto-Regressive models for time series using Binary or Quantized Data. IFAC Symposium on System Identification, Jul 2018, Stockholm, Sweden. pp.581-586, ⟨10.1016/j.ifacol.2018.09.221⟩. ⟨hal-01826047⟩
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