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  • 标题:Estimation of Auto-Regressive models for time series using Binary or Quantized Data
  • 本地全文:下载
  • 作者:R. Auber ; M. Pouliquen ; E. Pigeon
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:15
  • 页码:581-586
  • DOI:10.1016/j.ifacol.2018.09.221
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn 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.
  • 关键词:KeywordsAuto-Regressive modelTime seriesBinary SensorQuantized DataParameter estimation algorithm
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