Student’s t-Kernel-Based Maximum Correntropy Kalman Filter [PDF]
Sensors, 2022 The state estimation problem is ubiquitous in many fields, and the common state estimation method is the Kalman filter. However, the Kalman filter is based on the mean square error criterion, which can only capture the second-order statistics of the ...
Hongliang Huang, Hai Zhang
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Maximum Correntropy with Variable Center Unscented Kalman Filter for Robust Power System State Estimation [PDF]
Entropy, 2022 The robust Kalman filter with correntropy loss has received much attention in recent years for forecasting-aided state estimation in power systems, since it efficiently reduces the negative influence of various abnormal situations, such as non-Gaussian ...
Zhenglong Sun, Chuanlin Liu, Siyuan Peng
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Online Gradient Descent for Kernel-Based Maximum Correntropy Criterion [PDF]
Entropy, 2019 In the framework of statistical learning, we study the online gradient descent algorithm generated by the correntropy-induced losses in Reproducing kernel Hilbert spaces (RKHS).
Baobin Wang, Ting Hu
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Newtonian-Type Adaptive Filtering Based on the Maximum Correntropy Criterion [PDF]
Entropy, 2020 This paper provides a novel Newtonian-type optimization method for robust adaptive filtering inspired by information theory learning. With the traditional minimum mean square error (MMSE) criterion replaced by criteria like the maximum correntropy ...
Pengcheng Yue +3 more
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Maximum Correntropy Unscented Kalman Filter for Ballistic Missile Navigation System based on SINS/CNS Deeply Integrated Mode [PDF]
Sensors, 2018 Strap-down inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a high precision navigation technique for ballistic missiles. The traditional navigation method has a divergence in the position error.
Bowen Hou +4 more
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Maximum Correntropy Based Unscented Particle Filter for Cooperative Navigation with Heavy-Tailed Measurement Noises [PDF]
Sensors, 2018 In this paper, a novel robust particle filter is proposed to address the measurement outliers occurring in the multiple autonomous underwater vehicles (AUVs) based cooperative navigation (CN).
Ying Fan +4 more
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Diffusion Maximum Correntropy Criterion Based Robust Spectrum Sensing in Non-Gaussian Noise Environments [PDF]
Entropy, 2018 Spectrum sensing is the most important task in cognitive radio (CR). In this paper, a new robust distributed spectrum sensing approach, called diffusion maximum correntropy criterion (DMCC)-based robust spectrum sensing, is proposed for CR in the ...
Xiguang Xu +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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Kernel Adaptive Filters With Feedback Based on Maximum Correntropy
IEEE Access, 2018 This paper presents novel kernel adaptive filters with feedback, namely, kernel recursive maximum correntropy with multiple feedback (KRMC-MF) and its simplified version, a linear recurrent kernel online learning algorithm based on maximum correntropy ...
Shiyuan Wang +4 more
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A robust maximum correntropy forecasting model for time series with outliers [PDF]
PeerJ Computer Science, 2023 It is of great significance to develop a robust forecasting method for time series. The reliability and accuracy of the traditional model are reduced because the series is polluted by outliers.
Jing Ren, Wei-Qin Li
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