Identification of AR time‐series based on binary data
Author:
Affiliation:
1. Laboratoire d'Automatique de Caen ‐ EA 7478Normandie UnivUNICAEN, ENSICAEN, LAC14050Caen CedexFrance
2. Bodycap3 Rue du Dr Laennec14000CaenFrance
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-spr.2019.0152
Reference20 articles.
1. Figwer J.: ‘AR time‐series identification using quantized observations’.19th Int. Conf. on Methods and Models in Automation and Robotics Międzyzdroje Poland 2014
2. Estimation of the parameters in stationary autoregressive processes after hard limiting;Kedem B.;J. Am. Stat. Assoc.,1980
3. On goodness of fit of time series models: An application of higher order crossings
4. Estimation of autocorrelation in a binary time series;Damsleth E.;Stoch. Hydrol. Hydraul.,1988
5. Estimation of noisy quantized Gaussian AR time‐series with randomly varying observation coefficient;Krishnamurthy V.;IEEE Trans. Signal Process.,1995
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