Multirate systems and filter banks
Multirate systems and filter banks
Adaptive Filtering: Algorithms and Practical Implementation
Adaptive Filtering: Algorithms and Practical Implementation
Adaptive Filters
Selective partial update and set-membership subband adaptive filters
Signal Processing
Adaptive filtering in subbands using a weighted criterion
IEEE Transactions on Signal Processing
Fast Affine Projection Adaptation Algorithms With Stable and Robust Symmetric Linear System Slovers
IEEE Transactions on Signal Processing
Inherent Decorrelating and Least Perturbation Properties of the Normalized Subband Adaptive Filter
IEEE Transactions on Signal Processing
Nonuniform Subband Adaptive Filtering With Critical Sampling
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A new approach to subband adaptive filtering
IEEE Transactions on Signal Processing
A Variable Step-Size Affine Projection Algorithm Designed for Acoustic Echo Cancellation
IEEE Transactions on Audio, Speech, and Language Processing
Adaptive combination of subband adaptive filters with selective partial updates
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part I
Efficient Artifact Elimination in Cardiac Signals using Variable Step Size Adaptive Noise Cancellers
International Journal of Measurement Technologies and Instrumentation Engineering
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The normalized subband adaptive filter (NSAF) presented by Lee and Gan can obtain faster convergence rate than the normalized least-mean-square (NLMS) algorithm with colored input signals. However, similar to other fixed step-size adaptive filtering algorithms, the NSAF requires a tradeoff between fast convergence rate and low misadjustment. Recently, a set-membership NSAF (SM-NSAF) has been developed to address this problem. Nevertheless, in order to determine the error bound of the SM-NSAF, the power of the system noise should be known. In this paper, we propose a variable step-size matrix NSAF (VSSM-NSAF) from another point of view, i.e., recovering the powers of the subband system noises from those of the subband error signals of the adaptive filter, to further improve the performance of the NSAF. The VSSM-NSAF uses an effective system noise power estimate method, which can also be applied to the under-modeling scenario, and therefore need not know the powers of the subband system noises in advance. Besides, the steady-state mean-square behavior of the proposed algorithm is analyzed, which theoretically proves that the VSSM-NSAF can obtain a low misadjustment. Simulation results show good performance of the new algorithm as compared to other members of the NSAF family.