• DocumentCode
    2820011
  • Title

    System identification using quantized data

  • Author

    Agüero, Juan C. ; Goodwin, Graham C. ; Yuz, Juan I.

  • Author_Institution
    Univ. of Newcastle, Newcastle
  • fYear
    2007
  • fDate
    12-14 Dec. 2007
  • Firstpage
    4263
  • Lastpage
    4268
  • Abstract
    In this paper we consider the problem of identification of linear systems using quantized data. We argue that, where possible, it is desirable to not utilize "naively" quantized data but instead it is preferable to choose the quantization mechanism carefully. In particular, we show that using a generalized noise shaping coder improves the accuracy of the estimates. We examine the accuracy of estimates for both naive and coded quantizers.
  • Keywords
    linear systems; parameter estimation; quantisation (signal); white noise; coded quantizers; generalized noise shaping coder; linear system identification; naive quantizers; quantization mechanism; quantized data; white noise; Additive noise; Communication channels; Communication system control; Control systems; Linear systems; Noise shaping; Quantization; Signal processing; System identification; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2007 46th IEEE Conference on
  • Conference_Location
    New Orleans, LA
  • ISSN
    0191-2216
  • Print_ISBN
    978-1-4244-1497-0
  • Electronic_ISBN
    0191-2216
  • Type

    conf

  • DOI
    10.1109/CDC.2007.4434350
  • Filename
    4434350