72 citations · 163 across the 21 of their papers we have counts for
21 papers
Study of General Robust Subband Adaptive Filtering
Yi Yu, Hongsen He, Rodrigo C. de Lamare +1
In this paper, we propose a general robust subband adaptive filtering (GR-SAF) scheme against impulsive noise by minimizing the mean square deviation under the random-walk model wi…
Sparsity-Aware Robust Normalized Subband Adaptive Filtering algorithms based on Alternating Optimization
Yi Yu, Zongxin Huang, Hongsen He +2
This paper proposes a unified sparsity-aware robust normalized subband adaptive filtering (SA-RNSAF) algorithm for identification of sparse systems under impulsive noise. The propo…
Study of Robust Sparsity-Aware RLS algorithms with Jointly-Optimized Parameters for Impulsive Noise Environments
Y. Yu, L. Lu, Y. Zakharov +2
This paper proposes a unified sparsity-aware robust recursive least-squares RLS (S-RRLS) algorithm for the identification of sparse systems under impulsive noise. The proposed algo…
Conjugate Gradient Adaptive Learning with Tukey's Biweight M-Estimate
Lu Lu, Yi Yu, Rodrigo C. de Lamare +1
We propose a novel M-estimate conjugate gradient (CG) algorithm, termed Tukey's biweight M-estimate CG (TbMCG), for system identification in impulsive noise environments. In partic…
Study of filtered-x logarithmic recursive least -power algorithm
Z. Zheng, L. Lu, Y. Yu +2
For active impulsive noise control, a filtered-x recursive least -power (FxRLP) algorithm is proposed by minimizing the weighted summation of the -power of the \emph{a poster…
Study of Frequency domain exponential functional link network filters
T. Yu, S. Tana, R. C. de Lamareb +1
The exponential functional link network (EFLN) filter has attracted tremendous interest due to its enhanced nonlinear modeling capability. However, the computational complexity wil…
Active noise control techniques for nonlinear systems
Lu Lu, Kai-Li Yin, Rodrigo C. de Lamare +4
Most of the literature focuses on the development of the linear active noise control (ANC) techniques. However, ANC systems might have to deal with some nonlinear components and th…
A survey on active noise control techniques -- Part I: Linear systems
Lu Lu, Kai-Li Yin, Rodrigo C. de Lamare +4
Active noise control (ANC) is an effective way for reducing the noise level in electroacoustic or electromechanical systems. Since its first introduction in 1936, this approach has…
Study of Proximal Normalized Subband Adaptive Algorithm for Acoustic Echo Cancellation
Gang Guo, Yi Yu, Rodrigo C. de Lamare +3
In this paper, we propose a novel normalized subband adaptive filter algorithm suited for sparse scenarios, which combines the proportionate and sparsity-aware mechanisms. The prop…
Sparsity-Aware SSAF Algorithm with Individual Weighting Factors for Acoustic Echo Cancellation
Yi Yu, Tao Yang, Hongyang Chen +2
In this paper, we propose and analyze the sparsity-aware sign subband adaptive filtering with individual weighting factors (S-IWF-SSAF) algorithm, and consider its application in a…
Study of Diffusion Normalized Least Mean M-estimate Algorithms
Y. Yu, H. He, T. Yang +2
This work proposes diffusion normalized least mean M-estimate algorithm based on the modified Huber function, which can equip distributed networks with robust learning capability i…
Robust DCD-Based Recursive Adaptive Algorithms
Y. Yu, L. Lu, Z. Zheng +3
The dichotomous coordinate descent (DCD) algorithm has been successfully used for significant reduction in the complexity of recursive least squares (RLS) algorithms. In this work,…
Study of Robust Distributed Diffusion RLS Algorithms with Side Information for Adaptive Networks
Y. Yu, H. Zhao, R. C. de Lamare +2
This work develops robust diffusion recursive least squares algorithms to mitigate the performance degradation often experienced in networks of agents in the presence of impulsive…
Study of Robust Diffusion Recursive Least Squares Algorithms with Side Information for Networked Agents
Y. Yu, R. C. de Lamare, Y. Zakharov
This work develops a robust diffusion recursive least squares algorithm to mitigate the performance degradation often experienced in networks of agents in the presence of impulsive…
Study of Sparsity-Aware Subband Adaptive Filtering Algorithms with Adjustable Penalties
Y. Yu, H. Zhao, R. C. de Lamare
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 function…
Mean-Square Performance Analysis of Noise-Robust Normalized Subband Adaptive Filter Algorithm
Yi Yu, Haiquan Zhao, Badong Chen +2
This paper studies the statistical models of the noise-robust normalized subband adaptive filter (NR-NSAF) algorithm in the mean and mean square deviation senses involving transien…
A joint-optimization NSAF algorithm based on the first-order Markov model
Yi Yu, Haiquan Zhao
Recently, the normalized subband adaptive filter (NSAF) algorithm has attracted much attention for handling the colored input signals. Based on the first-order Markov model of the…
A Band-independent Variable Step Size Proportionate Normalized Subband Adaptive Filter Algorithm
Yi Yu, Haiquan Zhao
Proportionate-type normalized suband adaptive filter (PNSAF-type) algorithms are very attractive choices for echo cancellation. To further obtain both fast convergence rate and low…
Two improved normalized subband adaptive filter algorithms with good robustness against impulsive interferences
Yi Yu, Haiquan Zhao, Badong Chen +1
To improve the robustness of subband adaptive filter (SAF) against impulsive interferences, we propose two modified SAF algorithms with an individual scale function for each subban…
Set-membership improved normalized subband adaptive filter algorithms for acoustic echo cancellation
Yi Yu, Haiquan Zhao, Badong Chen
In order to improve the performances of recently-presented improved normalized subband adaptive filter (INSAF) and proportionate INSAF algorithms for highly noisy system, this pape…
A Novel Variable Step Size NLMS Algorithm Based on the Power Estimate of the System Noise
Yi Yu, Haiquan Zhao
To overcome the tradeoff of the conventional normalized least mean square (NLMS) algorithm between fast convergence rate and low steady-state misalignment, this paper proposes a va…