@inproceedings{5900615eaf2c4f67a90c54b002c4c594,
title = "AR time-series identification using quantized observations",
abstract = "In the paper an approach to AR time-series identification based on observations obtained using data acquisition system equipped with a quantizer having saturation is presented. In the presented approach AR time-series model identification is replaced by an ARMA time-series model identification that returns parameters of AR time-series. A focus on model identification for ultra low- and ultra high-power AR time-series is given. The presented discussion is illustrated by a simulation case study showing properties of the presented approach.",
author = "Jaros{\l}aw Figwer",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 19th International Conference on Methods and Models in Automation and Robotics, MMAR 2014 ; Conference date: 02-09-2014 Through 05-09-2014",
year = "2014",
month = nov,
day = "13",
doi = "10.1109/MMAR.2014.6957357",
language = "English",
series = "2014 19th International Conference on Methods and Models in Automation and Robotics, MMAR 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "235--239",
booktitle = "2014 19th International Conference on Methods and Models in Automation and Robotics, MMAR 2014",
address = "United States",
}