Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments
Sparse adaptive channel estimation problem is one of the most important topics in
broadband wireless communications systems due to its simplicity and robustness. So far …
broadband wireless communications systems due to its simplicity and robustness. So far …
Norm-adaption penalized least mean square/fourth algorithm for sparse channel estimation
Y Li, Y Wang, T Jiang - Signal processing, 2016 - Elsevier
A type of norm-adaption penalized least mean square/fourth (NA-LMS/F) algorithm is
proposed for sparse channel estimation applications. The proposed NA-LMS/F algorithm is …
proposed for sparse channel estimation applications. The proposed NA-LMS/F algorithm is …
Sparse-aware set-membership NLMS algorithms and their application for sparse channel estimation and echo cancelation
Y Li, Y Wang, T Jiang - AEU-International Journal of Electronics and …, 2016 - Elsevier
In this paper, we propose a type of sparsity-aware set-membership normalized least mean
square (SM-NLMS) algorithm for sparse channel estimation and echo cancelation. The …
square (SM-NLMS) algorithm for sparse channel estimation and echo cancelation. The …
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 …
Sparse least mean p-power algorithms for channel estimation in the presence of impulsive noise
The least mean p-power (LMP) is one of the most popular adaptive filtering algorithms. With
a proper p value, the LMP can outperform the traditional least mean square (p= 2)(p= 2) …
a proper p value, the LMP can outperform the traditional least mean square (p= 2)(p= 2) …
Vehicle engine noise cancellation based on a multi-channel fractional-order active noise control algorithm
T Li, M Wang, Y He, N Wang, J Yang, R Ding, K Zhao - Machines, 2022 - mdpi.com
For the problem of low-frequency noise suppression in a large area of the vehicle space, this
paper proposes a novel multi-channel fractional-order active noise control algorithm and …
paper proposes a novel multi-channel fractional-order active noise control algorithm and …
Low-complexity non-uniform penalized affine projection algorithm for sparse system identification
Y Li, C Zhang, S Wang - Circuits, Systems, and Signal Processing, 2016 - Springer
In this paper, an improved sparse-aware affine projection (AP) algorithm for sparse system
identification is proposed and investigated. The proposed sparse AP algorithm is realized by …
identification is proposed and investigated. The proposed sparse AP algorithm is realized by …
Robust proportionate adaptive filter based on maximum correntropy criterion for sparse system identification in impulsive noise environments
Proportionate-type adaptive filtering (PtAF) algorithms have been successfully applied to
sparse system identification. The major drawback of the traditional PtAF algorithms based on …
sparse system identification. The major drawback of the traditional PtAF algorithms based on …
Recursive generalized maximum correntropy criterion algorithm with sparse penalty constraints for system identification
To address the sparse system identification problem in a non‐Gaussian impulsive noise
environment, the recursive generalized maximum correntropy criterion (RGMCC) algorithm …
environment, the recursive generalized maximum correntropy criterion (RGMCC) algorithm …
Mean-square deviation analysis of the zero-attracting variable step-size LMS algorithm
The well-known variable step-size least-mean-square (VSSLMS) algorithm provides faster
convergence rate while maintaining lower mean-square error than the conventional LMS …
convergence rate while maintaining lower mean-square error than the conventional LMS …