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Article Dans Une Revue IET Signal Processing Année : 2019

Identification of AR Time-series based on binary data

Résumé

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.

Dates et versions

hal-02323954 , version 1 (21-10-2019)

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Citer

Romain Auber, Mathieu Pouliquen, Eric Pigeon, Olivier Gehan, Mohammed M'Saad, et al.. Identification of AR Time-series based on binary data. IET Signal Processing, 2019, 14 (1), pp.24-31. ⟨10.1049/iet-spr.2019.0152⟩. ⟨hal-02323954⟩
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