Constrained maximum correntropy adaptive filtering
نویسندگان
چکیده
منابع مشابه
Constrained maximum correntropy adaptive filtering
Constrained adaptive filtering algorithms inculding constrained least mean square (CLMS), constrained affine projection (CAP) and constrained recursive least squares (CRLS) have been extensively studied in many applications. Most existing constrained adaptive filtering algorithms are developed under mean square error (MSE) criterion, which is an ideal optimality criterion under Gaussian noises....
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The maximum correntropy criterion (MCC) has recently been successfully applied to adaptive filtering. Adaptive algorithms under MCC show strong robustness against large outliers. In this work, we apply the MCC criterion to develop a robust Hammerstein adaptive filter. Compared with the traditional Hammerstein adaptive filters, which are usually derived based on the well-known mean square error ...
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To address sparse channel estimation problem in nonGaussian impulsive noise environment, a recursive maximum correntropy criteria (RMCC) algorithm using sparse constraint is proposed to combat impulsive-inducing instability. Specifically, the recursive algorithm on the correntrioy with a forgetting factor of error at iteration is to solve steady-state error for improving the maximum correntropy...
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1. Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, 710049, China 2. School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China 3. Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611 USA Abstract—As a robust nonlinear similarity measure in kernel space, correntropy has received increasing attent...
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ژورنال
عنوان ژورنال: Signal Processing
سال: 2017
ISSN: 0165-1684
DOI: 10.1016/j.sigpro.2017.05.009