• DocumentCode
    1746814
  • Title

    Adaptive filtering algorithms

  • Author

    Theodoridis, Sergios

  • Author_Institution
    Dept. of Inf. & Telecommun., Athens Univ., Greece
  • Volume
    3
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1497
  • Abstract
    System identification (SI) is the task of specifying an unknown system´s model in terms of the available experimental evidence, that is a set of input-desired output response signal samples. System identification is a central issue in a large number of application areas, such as control, channel equalization, echo cancellation. This state-of-the-art article focuses on systems that can be modeled in terms of a Finite Impulse Response (FIR) and its goal is to present the available palette of adaptive SI algorithms in a unifying way
  • Keywords
    FIR filters; adaptive filters; filtering theory; identification; adaptive filtering algorithm; finite impulse response filter; system identification; Adaptive filters; Approximation algorithms; Cost function; Filtering algorithms; Finite impulse response filter; Iterative algorithms; Least squares approximation; Stochastic processes; System identification; Wiener filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference, 2001. IMTC 2001. Proceedings of the 18th IEEE
  • Conference_Location
    Budapest
  • ISSN
    1091-5281
  • Print_ISBN
    0-7803-6646-8
  • Type

    conf

  • DOI
    10.1109/IMTC.2001.929455
  • Filename
    929455