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Journal ArticleDOI

A new approach to subband adaptive filtering

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TLDR
This paper proposes a new structure and a new formulation for adapting the filter coefficients based on polyphase decomposition of the filter to be adapted and is independent of the type of filter banks used in the subband decomposition.
Abstract
Subband adaptive filtering has attracted much attention lately. In this paper, we propose a new structure and a new formulation for adapting the filter coefficients. This structure is based on polyphase decomposition of the filter to be adapted and is independent of the type of filter banks used in the subband decomposition. The new formulation yields improved convergence rate when the LMS algorithm is used for coefficient adaptation. As we increase the number of bands in the filter, the convergence rate increases and approaches the rate that can be obtained with a flat input spectrum. The computational complexity of the proposed scheme is nearly the same as that of the fullband approach. Simulation results are included to demonstrate the efficacy of the new approach.

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Citations
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Journal ArticleDOI

Improving convergence of the NLMS algorithm using constrained subband updates

TL;DR: Compared to the classical fullband least-mean-square (LMS) algorithm, the subband adaptive filtering algorithm derived from the proposed criterion exhibits faster convergence under colored excitation.
Journal ArticleDOI

System Identification in the Short-Time Fourier Transform Domain With Crossband Filtering

TL;DR: It is shown that increasing the number of crossband filters not necessarily implies a lower steady-state mean-square error (mse) in subbands, and analytical relations between the number and length of the input signal are derived.
Journal ArticleDOI

A Variable Step-Size Matrix Normalized Subband Adaptive Filter

TL;DR: This paper proposes a variable step-size matrix NSAF (VSSM-NSAF) from another point of view, i.e., recovering the powers of theSubband system noises from those of the subband error signals of the adaptive filter, to further improve the performance of the NSAF.
Journal ArticleDOI

Inherent Decorrelating and Least Perturbation Properties of the Normalized Subband Adaptive Filter

TL;DR: This correspondence describes and analyzes a class of subband adaptive filters (SAFs) that stems from various approaches of applying subband and multirate techniques in adaptive filtering, called the normalized SAF (NSAF), which has a unique weight-control mechanism.
Journal ArticleDOI

New structures for adaptive filtering in subbands with critical sampling

TL;DR: A new family of adaptive structures with critical sampling of the subband signals, which can also yield exact modeling, is obtained based on the results obtained for the sparse subfilter structure.
References
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Book

Multirate Systems and Filter Banks

TL;DR: In this paper, a review of Discrete-Time Multi-Input Multi-Output (DIMO) and Linear Phase Perfect Reconstruction (QLP) QMF banks is presented.
Journal ArticleDOI

Adaptive noise cancelling: Principles and applications

TL;DR: It is shown that in treating periodic interference the adaptive noise canceller acts as a notch filter with narrow bandwidth, infinite null, and the capability of tracking the exact frequency of the interference; in this case the canceller behaves as a linear, time-invariant system, with the adaptive filter converging on a dynamic rather than a static solution.
Journal ArticleDOI

Adaptive filtering in subbands with critical sampling: analysis, experiments, and application to acoustic echo cancellation

TL;DR: In this article, an exact analysis of the critically subsampled two-band modelization scheme is given, and it is demonstrated that adaptive cross-filters between the subbands are necessary for modelization with small output errors.

Adaptive Filtering in Subbands with Critical Sampling: Analysis, Experiments, and Application to Acoustic

TL;DR: An exact analysis of the critically subsampled two-band modelization scheme is given, and it is demonstrated that adaptive cross-filters between the subbands are necessary for modelization with small output errors.