Adaptive filtering using Higher Order Statistics (HOS)
The performed job, in this study, consists in studying adaptive filters and higher order statistics (HOS) to ameliorate their performances, by extension of linear case to non linear filters via Volterra series.
This study is, principally, axed on:
„ Choice of the adaptation step and convergence conditions.
„ Convergence rate.
„ Adaptive variation of the convergence factor, according to the input signal.
The obtained results, with real signals, have shown computationally efficient and numerically stable algorithms for adaptive nonlinear filtering while keeping relatively simple computational complexity.
Keywords: Convergence factor, Adaptive filtering, Equalization, Higher Order Statistics (HOS), non linear filters, Volterra series.
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ABOUT THE AUTHORS
Abdelghani Manseur
Department of Electrical Engineering, Kasdi Merbah University Ouargla, Algeria
Daoud Berkani
Department of Electronics, Polytechnical National School Algiers, Algeria
Abdenour Mekhmoukh
Department of Electrical Engineering, Abderahmane Mira University Bejaia, Algeria
Abdelghani Manseur
Department of Electrical Engineering, Kasdi Merbah University Ouargla, Algeria
Daoud Berkani
Department of Electronics, Polytechnical National School Algiers, Algeria
Abdenour Mekhmoukh
Department of Electrical Engineering, Abderahmane Mira University Bejaia, Algeria
