Fast communication: Steady-state mean-square error analysis of regularized normalized subband adaptive filters

Authors:
Jingen Ni;Xiaoping Chen
Affiliations:
-;-
Venue:
Signal Processing
Year:
2013

Citing 6
Cited 1

Multirate systems and filter banks

Multirate systems and filter banks
Distributed average consensus with least-mean-square deviation

Journal of Parallel and Distributed Computing
Inherent Decorrelating and Least Perturbation Properties of the Normalized Subband Adaptive Filter

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Mean-square performance of a family of affine projection algorithms

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Mean-Square Deviation Analysis of Affine Projection Algorithm

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On Regularization in Adaptive Filtering

IEEE Transactions on Audio, Speech, and Language Processing

Fast communication: Two variants of the sign subband adaptive filter with improved convergence rate

Signal Processing

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Abstract

The normalized subband adaptive filter (NSAF) has faster convergence rate than the normalized least-mean-square (NLMS) algorithm for colored input signals. Regularization of the NSAF is of importance in practical applications. In this paper, we analyze the steady-state mean-square error (MSE) of regularized NSAFs. The analysis is carried out based on the derivation of a variable regularization matrix NSAF (VRM-NSAF). Theoretical expressions for the steady-state MSE of two regularized NSAFs are derived under some assumptions. Simulation results are given to support the theoretical analysis.