• DocumentCode
    66647
  • Title

    Identification of FIR Systems Based on Quantized Output Measurements: A Quadratic Programming-Based Method

  • Author

    Jiandong Wang ; Qinghua Zhang

  • Author_Institution
    Coll. of Eng., Peking Univ., Beijing, China
  • Volume
    60
  • Issue
    5
  • fYear
    2015
  • fDate
    May-15
  • Firstpage
    1439
  • Lastpage
    1444
  • Abstract
    This technical note proposes a quadratic programming (QP)-based method for identification of finite impulse response (FIR) dynamic systems from quantized or binary data. The main idea of the proposed method is to reformulate this identification problem, usually viewed as a nonlinear estimation problem with discontinuous nonlinearities, in the form of a standard QP problem, which is a convex optimization problem and can be solved efficiently. The so-called complete input conditions to ensure the unique solution of the QP problem are developed, and the consistency of the estimated parameters is established under the complete input conditions. Numerical examples demonstrate the effectiveness of the proposed method.
  • Keywords
    convex programming; identification; quadratic programming; FIR system identification; QP-based method; convex optimization; finite impulse response; quadratic programming-based method; quantized output measurement; Face; Finite impulse response filters; Level set; Matrix decomposition; Quantization (signal); Standards; Vectors; Quadratic programming (QP); quantized data; system identification;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2014.2357133
  • Filename
    6897934