780 citations · 1.2k across the 23 of their papers we have counts for
23 papers
Robust Total Least Mean M-Estimate normalized subband filter Adaptive Algorithm for impulse noises and noisy inputs
Haiquan Zhao, Zian Cao, Yida Chen
When the input signal is correlated input signals, and the input and output signal is contaminated by Gaussian noise, the total least squares normalized subband adaptive filter (TL…
Robust Multitask Diffusion Normalized M-estimate Subband Adaptive Filtering Algorithm Over Adaptive Networks
Wenjing Xu, Haiquan Zhao, Shaohui Lv
In recent years, the multitask diffusion least mean square (MD-LMS) algorithm has been extensively applied in the distributed parameter estimation and target tracking of multitask…
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…
Set-membership NLMS algorithm based on bias-compensated and regression noise variance estimation for noisy inputs
Kaili Yin, Haiquan Zhao, Lu Lu
The bias-compensated set-membership normalised LMS (BCSMNLMS) algorithm is proposed based on the concept of set-membership filtering, which incorporates the bias-compensation techn…
Diffusion Leaky Zero Attracting Least Mean Square Algorithm and Its Performance Analysis
Long Shi, Haiquan Zhao
Recently, the leaky diffusion least-mean-square (DLMS) algorithm has obtained much attention because of its good performance for high input eigenvalue spread and low signal-to-nois…
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…
Robustness of Maximum Correntropy Estimation Against Large Outliers
Badong Chen, Lei Xing, Haiquan Zhao +2
The maximum correntropy criterion (MCC) has recently been successfully applied in robust regression, classification and adaptive filtering, where the correntropy is maximized inste…
Adaptive beamforming method based on recursive maximum correntropy in impulsive noise with alpha-stable process
Lu Lu, Haiquan Zhao
As a well-established adaptation criterion, the maximum correntropy criterion (MCC) has been receiving increasing attention due to its robust against outliers. In this paper, a new…
Subband adaptive filter trained by differential evolution for channel estimation
Lu Lu, Haiquan Zhao
The normalized subband adaptive filter (NSAF) is widely accepted as a preeminent adaptive filtering algorithm because of its efficiency under the colored excitation. However, the c…
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…
Kernel Risk-Sensitive Loss: Definition, Properties and Application to Robust Adaptive Filtering
Badong Chen, Lei Xing, Bin Xu +3
Nonlinear similarity measures defined in kernel space, such as correntropy, can extract higher-order statistics of data and offer potentially significant performance improvement ov…
A Class of Diffusion Algorithms with Logarithmic Cost over Adaptive Sparse Volterra Network
Lu Lu, Haiquan Zhao
In this Letter, we present a novel class of diffusion algorithms that can be used to estimate the coefficients of sparse Volterra network (SVN). The development of the algorithms i…
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…
KLMAT: A Kernel Least Mean Absolute Third Algorithm
Lu Lu, Haiquan Zhao, Badong Chen
In this paper, a kernel least mean absolute third (KLMAT) algorithm is developed for adaptive prediction. Combining the benefits of the kernel method and the least mean absolute th…
Diffusion leaky LMS algorithm: analysis and implementation
Lu Lu, Haiquan Zhao
The diffusion least-mean square (dLMS) algorithms have attracted much attention owing to its robustness for distributed estimation problems. However, the performance of such filter…
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…
Variable-mixing parameter quantized kernel robust mixed-norm algorithms for combating impulsive interference
Lu Lu, Haiquan Zhao, Badong Chen
Although the kernel robust mixed-norm (KRMN) algorithm outperforms the kernel least mean square (KLMS) algorithm in impulsive noise, it still has two major problems as follows: (1)…
A novel normalized sign algorithm for system identification under impulsive noise interference
Lu Lu, Haiquan Zhao, Kan Li +1
To overcome the performance degradation of adaptive filtering algorithms in the presence of impulsive noise, a novel normalized sign algorithm (NSA) based on a convex combination s…
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…
Generalized Correntropy for Robust Adaptive Filtering
Badong Chen, Lei Xing, Haiquan Zhao +2
As a robust nonlinear similarity measure in kernel space, correntropy has received increasing attention in domains of machine learning and signal processing. In particular, the max…