• DocumentCode
    356769
  • Title

    A genetic approach to ARMA filter synthesis for EEG signal simulation

  • Author

    Janeczko, C. ; Lopes, Heitor S.

  • Author_Institution
    Dept. of Electron., CEFET-PR, Brazil
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    373
  • Abstract
    This paper describes the computational simulation of an electroencephalographic (EEG) signal (background activity, alpha waves) by filtering a white noise with an ARMA (Autoregressive Moving Average) filter. The filter coefficients were obtained interactively using genetic algorithms, comparing the spectrum of a real and a simulated signal. Results demonstrate the feasibility of the technique
  • Keywords
    autoregressive moving average processes; electroencephalography; filtering theory; genetic algorithms; medical signal processing; white noise; ARMA filter synthesis; EEG signal simulation; alpha waves; autoregressive moving average filter; background activity; computational simulation; electroencephalographic signal; genetic algorithms; white noise; Autoregressive processes; Brain modeling; Computational modeling; Differential equations; Electroencephalography; Filtering; Filters; Genetics; Signal synthesis; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
  • Conference_Location
    La Jolla, CA
  • Print_ISBN
    0-7803-6375-2
  • Type

    conf

  • DOI
    10.1109/CEC.2000.870319
  • Filename
    870319