Robust proportionate normalized least mean M-estimate algorithm for block-sparse system identification
S Lv, H Zhao, L Zhou - … Transactions on Circuits and Systems II …, 2021 - ieeexplore.ieee.org
In practical applications, the impulse responses (IRs) of some network echo paths are
blocksparse (BS), while the traditional proportionate and zero attraction algorithms do not …
blocksparse (BS), while the traditional proportionate and zero attraction algorithms do not …
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 …
Robust constrained recursive least M-estimate adaptive filtering algorithm
W Xu, H Zhao - Signal Processing, 2022 - Elsevier
Recently, the constrained adaptive filtering algorithms with strong robustness to non-
Gaussian noise have been widely studied. Among them, the robust constrained least mean …
Gaussian noise have been widely studied. Among them, the robust constrained least mean …
Multi-layered recursive least squares for time-varying system identification
Traditional recursive least squares (RLS) adaptive filtering is widely used to estimate the
impulse responses (IR) of an unknown system. Nevertheless, the RLS estimator shows poor …
impulse responses (IR) of an unknown system. Nevertheless, the RLS estimator shows poor …
A new recursive dynamic factor analysis for point and interval forecast of electricity price
The functional principal component analysis (FPCA) is a recent tool in multivariate statistics
and it has been shown to be effective for electricity price forecasting. However, its online …
and it has been shown to be effective for electricity price forecasting. However, its online …
Affine projection M-estimate subband adaptive filters for robust adaptive filtering in impulsive noise
We propose an affine projection M-estimate subband adaptive filter (APM-SAF), which is
characterized by its robustness against impulsive noise. Instead of the conventional mean …
characterized by its robustness against impulsive noise. Instead of the conventional mean …
A real-time recursion correction hybrid linear state estimator using stream processing
This study intends to improve the accuracy, efficiency, and timeliness of state estimation (SE)
for large-scale electric power systems by presenting a recursion correction hybrid linear …
for large-scale electric power systems by presenting a recursion correction hybrid linear …
Robust recursive least-squares adaptive-filtering algorithm for impulsive-noise environments
MZA Bhotto, A Antoniou - IEEE Signal processing letters, 2011 - ieeexplore.ieee.org
A new robust recursive least-squares (RLS) adaptive filtering algorithm that uses a priori
error-dependent weights is proposed. Robustness against impulsive noise is achieved by …
error-dependent weights is proposed. Robustness against impulsive noise is achieved by …
Proportionate M-estimate adaptive filtering algorithms: Insights and improvements
In the literature, the proportionate least mean M-estimate (PLMM) algorithm exhibits good
performance when dealing with sparse systems in the presence of impulsive noises. In this …
performance when dealing with sparse systems in the presence of impulsive noises. In this …
A fast robust recursive least-squares algorithm
We present a fast robust recursive least-squares (FRRLS) algorithm based on a recently
introduced new framework for designing robust adaptive filters. The algorithm is the result of …
introduced new framework for designing robust adaptive filters. The algorithm is the result of …