Generalized Correntropy for Robust_newline Adaptive Filtering
نویسندگان
چکیده
منابع مشابه
Generalized Correntropy for Robust Adaptive Filtering
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...
متن کاملConstrained 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....
متن کاملMaximum Correntropy Adaptive Filtering Approach for Robust Compressive Sensing Reconstruction
Robust compressive sensing(CS) reconstruction has become an attractive research topic in recent years. Robust CS aims to reconstruct the sparse signals under non-Gaussian(i.e. heavy tailed) noises where traditional CS reconstruction algorithms may perform very poorly due to utilizing l2 norm of the residual vector in optimization. Most of existing robust CS reconstruction algorithms are based o...
متن کاملRobust Hammerstein Adaptive Filtering under Maximum Correntropy Criterion
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 ...
متن کاملProportionate Adaptive Filtering under Correntropy Criterion in Impulsive Noise Environments
An improved proportionate adaptive filter based on the Maximum Correntropy Criterion (IP-MCC) is proposed for identifying the system with variable sparsity in an impulsive noise environment. Utilization of MCC mitigates the effect of impulse noise while the improved proportionate concepts exploit the underlying system sparsity to improve the convergence rate. Performance analysis of the propose...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2016
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2016.2539127