Discrete wavelet transform-based RI adaptive algorithm for system identification

Mohammad Shukri Salman, Alaa Eleyan, Bahaa Al-Sheikh


In this paper, we propose a new adaptive filtering algorithm for system identification. The algorithm is based on the recursive inverse (RI) adaptive algorithm which suffers from low convergence rates in some applications; i.e., the eigenvalue spread of the autocorrelation matrix is relatively high. The proposed algorithm applies discrete-wavelet transform (DWT) to the input signal which, in turn, helps to overcome the low convergence rate of the RI algorithm with relatively small step-size(s). Different scenarios has been investigated in different noise environments in system identification setting. Experiments demonstrate the advantages of the proposed DWT recursive inverse (DWT-RI) filter in terms of convergence rate and mean-square-error (MSE) compared to the RI, discrete cosine transform LMS (DCTLMS), discrete-wavelet transform LMS (DWT-LMS) and recursive-least-squares (RLS) algorithms under same conditions.


Adaptive Filters; Recursive Inverse Algorithm; Discrete Wavelet Transform; LMS Algorithm; System Identification

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DOI: http://doi.org/10.11591/ijece.v10i3.pp2383-2391
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ISSN 2088-8708, e-ISSN 2722-2578