NDLI: A variable step-size pre-filter-bank adaptive algorithm

Content Provider	IEEE Xplore Digital Library
Author	Ting Liu Gazor, S.
Copyright Year	1993
Abstract	To improve the convergence speed and reduce the mean-square error (MSE) of the gradient based adaptive algorithms in colored environments, such as acoustic echo cancellation, a pre-filter-bank (PFB) adaptive algorithm is proposed by minimizing a weighted criterion of squared errors in subbands. The optimal solution obtained by minimizing this criterion is the Wiener filter, independent of the weights. However, these weights have a strong impact on the behavior of the algorithm and have relations with the subband step-sizes. In particular, the optimal weights, which are derived for a random walk time-varying plant in this paper, depend on the spectra of the input signal and the additive noise. Without a priori knowledge of the spectra, for faster initial convergence and better tracking performance in nonstationary environments, a simple variable step-size (VS) algorithm is introduced to the PFB algorithm in each subband for adjusting the subband step-sizes. This new multistep-size algorithm, which is called the variable step-size pre-filter-bank (VSP) algorithm, improves significantly over the traditional full-band VS algorithms in colored environments. The more colored the noise and the input signal, the more significant the improvement. The drawback of this algorithm is the increase of the computational complexity. As the filters in the filter bank are commonly narrow-band; the nondecimated outputs of these filters are highly correlated. This correlation permits us to approximate the subband autocorrelation matrices by single rank matrices to reduce the computational complexity of the algorithm. The simplified version has almost the same performance as the original VSP algorithm. Simulations show that the proposed algorithms are more efficient than LMS in terms of tracking capabilities for colored environments.
Starting Page	905
Ending Page	916
Page Count	12
File Size	479315
File Format	PDF
ISSN	10636676
Volume Number	13
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptive algorithm Filter bank Computational complexity Mean square error methods Echo cancellers Wiener filter Additive noise Convergence Colored noise Working environment noise tracking Adaptive signal processing colored noise decorrelation echo suppression filterbank least mean squares methods
Content Type	Text
Resource Type	Article
Subject	Acoustics and Ultrasonics Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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