Our robust constrained-LMS algorithm provides excellent robustness against the desired signal mismatches, offers fast convergence rate and makes the mean output ...
Our robust constrained-LMS algorithm provides excellent robustness against signal steering vector mismatches, offers fast convergence rate and makes the mean ...
The constrained least mean square (CLMS) algorithm [4] is the simplest and most classic constrained algorithm, it not only has low computational complexity, but ...
Abstract—The so-called constrained least mean-square algorithm is one of the most commonly used linear-equality- constrained adaptive filtering algorithms.
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In the paper, an approach is proposed for robust constrained LMS beamforming in the presence of pointing error, array geometry error and sensor phase error ...
In this paper, on the basis of the CLMS algorithm, we develop a novel robust constrained-LMS (RCLMS) algorithm against the signal steering vector mismatches and ...
The so-called constrained least mean-square algorithm is one of the most commonly used linear-equality-constrained adaptive filtering algorithms.
INTRODUCTION. Adaptive beamformers can be used, with minimal a priori information, to greatly improve the signal-to-noise ratio of a signal in the prescence ...
This noise constrained LMS (NCLMS) algorithm is a type of variable step-size LMS algorithm, which is derived by adding constraints to the mean-square error ...
In this paper, we develop a robust constrained-LMS (RCLMS) algorithm based on worst-case SINR maximization. Our algorithm belongs to the class of diagonal ...