Results 21 to 30 of about 543 (157)
Sparse-Aware Bias-Compensated Adaptive Filtering Algorithms Using the Maximum Correntropy Criterion for Sparse System Identification with Noisy Input [PDF]
Entropy, 2018 To address the sparse system identification problem under noisy input and non-Gaussian output measurement noise, two novel types of sparse bias-compensated normalized maximum correntropy criterion algorithms are developed, which are capable of ...
Wentao Ma +5 more
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Maximum Total Improper Complex Correntropy Algorithm for Widely Linear Adaptive Filtering
IEEE Access, 2022 The maximum total complex correntropy (MTCC) algorithm improves the performance of adaptive filtering under the error in variable (EIV) model by integrating both input and output noise information into the total complex correntropy.
Lianqing Fu, Li Zhou
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Remote Sensing, 2022 To improve the accuracy of the maximum correntropy Kalman filter (MCKF) in wireless sensors networks (WSNs) positioning, a dynamic self-tuning maximum correntropy Kalman filter (DSTMCKF) is proposed, where innovation and the sensors information of the ...
Tianrui Liao +4 more
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Generalized Asymmetric Correntropy for Robust Adaptive Filtering: A Theoretical and Simulation Study
Remote Sensing, 2022 Correntropy has been proved to be effective in eliminating the adverse effects of impulsive noises in adaptive filtering. However, correntropy is not desirable when the error between the two random variables is asymmetrically distributed around zero.
Hua Qu +5 more
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Adaptive Robust Unscented Kalman Filter via Fading Factor and Maximum Correntropy Criterion [PDF]
Sensors, 2018 Yuanqing Xia +2 more
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ADMM for maximum correntropy criterion [PDF]
2016 International Joint Conference on Neural Networks (IJCNN), 2016 The correntropy provides a robust criterion for outlier-insensitive machine learning, and its maximisation has been increasingly investigated in signal and image processing. In this paper, we investigate the problem of unmixing hyperspectral images, namely decomposing each pixel/spectrum of a given image as a linear combination of other pixels/spectra ...
Zhu, Fei +4 more
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Regularized maximum correntropy machine [PDF]
Neurocomputing, 2015 In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples.
Jim Jing-Yan Wang +3 more
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Cognitive Computation and Systems, 2022 Aiming at meetiing the need to filtering flight trajectory data for aircraft testing, a novel adaptive cubature Kalman filter (CKF) is proposed based on the maximum correntropy and Gaussian‐sum in this paper.
Jing G. Bai +4 more
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Constrained maximum correntropy adaptive filtering [PDF]
Signal Processing, 2017 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 ...
Siyuan Peng +4 more
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Entropy, 2020 The complex correntropy has been successfully applied to complex domain adaptive filtering, and the corresponding maximum complex correntropy criterion (MCCC) algorithm has been proved to be robust to non-Gaussian noises.
Fei Dong, Guobing Qian, Shiyuan Wang
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