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Maximum correntropy unscented filter [PDF]
International Journal of Systems Science, 2017 The unscented transformation (UT) is an efficient method to solve the state estimation problem for a non-linear dynamic system, utilizing a derivative-free higher-order approximation by approximating a Gaussian distribution rather than approximating a non-linear function.
Liu, Xi +4 more
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Maximum correntropy Kalman filter [PDF]
Automatica, 2017 Traditional Kalman filter (KF) is derived under the well-known minimum mean square error (MMSE) criterion, which is optimal under Gaussian assumption. However, when the signals are non-Gaussian, especially when the system is disturbed by some heavy-tailed impulsive noises, the performance of KF will deteriorate seriously.
Chen, Badong +3 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 ...
Peng, Siyuan +4 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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Variational Bayesian-Based Improved Maximum Mixture Correntropy Kalman Filter for Non-Gaussian Noise
Entropy, 2022 The maximum correntropy Kalman filter (MCKF) is an effective algorithm that was proposed to solve the non-Gaussian filtering problem for linear systems.
Xuyou Li, Yanda Guo, Qingwen Meng
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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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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.
Wang, Jim Jing-Yan +3 more
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Broad Learning System Based on Maximum Correntropy Criterion [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2021 As an effective and efficient discriminative learning method, Broad Learning System (BLS) has received increasing attention due to its outstanding performance in various regression and classification problems. However, the standard BLS is derived under the minimum mean square error (MMSE) criterion, which is, of course, not always a good choice due to ...
Yunfei Zheng +3 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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Maximum Correntropy Criterion With Variable Center [PDF]
IEEE Signal Processing Letters, 2019 5 pages, 1 ...
Badong Chen +3 more
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