• DocumentCode
    180563
  • Title

    Monte Carlo limit cycle characterization

  • Author

    Luengo, D. ; Oses, David ; Martino, Luca

  • Author_Institution
    Dept. of Circuits & Sytems Eng., Univ. Politec. de Madrid, Madrid, Spain
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    8043
  • Lastpage
    8047
  • Abstract
    The fixed point implementation of IIR digital filters usually leads to the appearance of zero-input limit cycles, which degrade the performance of the system. In this paper, we develop an efficient Monte Carlo algorithm to detect and characterize limit cycles in fixed-point IIR digital filters. The proposed approach considers filters formulated in the state space and is valid for any fixed point representation and quantization function. Numerical simulations on several high-order filters, where an exhaustive search is unfeasible, show the effectiveness of the proposed approach.
  • Keywords
    IIR filters; Monte Carlo methods; limit cycles; quantisation (signal); state-space methods; Monte Carlo algorithm; Monte Carlo limit cycle characterization; fixed point implementation; fixed point representation; fixed-point IIR digital filters; high-order filters; quantization function; state space; zero-input limit cycles; Limit-cycles; Monte Carlo methods; Passband; Proposals; Quantization (signal); Signal processing algorithms; IIR filters; Monte Carlo methods; finite wordlength effects; limit cycles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6855167
  • Filename
    6855167