Diffusion normalized least mean M-estimate algorithms: Design and performance analysis
This work proposes diffusion normalized least mean M-estimate algorithm based on the
modified Huber function, which can equip distributed networks with robust learning …
modified Huber function, which can equip distributed networks with robust learning …
Proportionate RLS with l1 norm regularization: Performance analysis and fast implementation
Sparse recursive least squares (RLS) adaptive filter algorithms achieve faster convergence
and better performance than the standard RLS algorithm under sparse systems. Existing …
and better performance than the standard RLS algorithm under sparse systems. Existing …
Robust set-membership normalized subband adaptive filtering algorithms and their application to acoustic echo cancellation
This paper presents a family of robust set-membership normalized subband adaptive
filtering (RSM-NSAF) algorithms for acoustic echo cancellation (AEC). By using a new robust …
filtering (RSM-NSAF) algorithms for acoustic echo cancellation (AEC). By using a new robust …
Variable Step-Size -Norm Constraint NLMS Algorithms Based on Novel Mean Square Deviation Analyses
This paper proposes variable step-size-norm constraint normalized least mean square (-
NLMS) algorithms for sparse channel identification. The mean square deviation of the-NLMS …
NLMS) algorithms for sparse channel identification. The mean square deviation of the-NLMS …
Variable step-size saturation affine projection algorithm against impulsive noise
This study proposes a variable step-size saturation affine projection algorithm (VSS-sat-
APA) robust to impulsive noise. The proposed algorithm is analytically derived from the …
APA) robust to impulsive noise. The proposed algorithm is analytically derived from the …
Sparsity-aware subband adaptive algorithms with adjustable penalties
We propose two sparsity-aware normalized subband adaptive filter (NSAF) algorithms by
using the gradient descent method to minimize a combination of the original NSAF cost …
using the gradient descent method to minimize a combination of the original NSAF cost …
Exact expectation analysis of the deficient-length LMS algorithm
P Lara, LDTJ Tarrataca, DB Haddad - Signal Processing, 2019 - Elsevier
Stochastic models that predict adaptive filtering algorithms performance usually employ
several assumptions in order to simplify the analysis. Although these simplifications facilitate …
several assumptions in order to simplify the analysis. Although these simplifications facilitate …
Sparsity-promoting affine projection algorithm with periodically-updated gain matrix and its performance analysis
J Ni, N Zhang, H Li - IEEE/ACM Transactions on Audio, Speech …, 2023 - ieeexplore.ieee.org
Sparse system identification is often encountered in applications such as network and
acoustic echo cancellation. This work applies the sparsity promoting method to the affine …
acoustic echo cancellation. This work applies the sparsity promoting method to the affine …
Bias compensated zero attracting normalized least mean square adaptive filter and its performance analysis
This paper presents a new normalized least mean square (NLMS) algorithm for sparse
system identification where the input signal is corrupted by white measurement noise. The …
system identification where the input signal is corrupted by white measurement noise. The …
Diffusion proportionate affine projection sign algorithm for distributed estimation over network
This paper proposes a diffusion proportionate affine projection sign algorithm for distributed
estimation of sparse vector over network. The algorithm is derived by minimizing l 1-norm …
estimation of sparse vector over network. The algorithm is derived by minimizing l 1-norm …