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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Frequency domain maximum correntropy criterion spline adaptive filtering [PDF]
Scientific Reports, 2021 A filtering algorithm based on frequency domain spline type, frequency domain spline adaptive filters (FDSAF), effectively reducing the computational complexity of the filter.
Wenyan Guo, Yongfeng Zhi, Kai Feng
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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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Maximum Correntropy Criterion with Distributed Method [PDF]
Mathematics, 2022 The Maximum Correntropy Criterion (MCC) has recently triggered enormous research activities in engineering and machine learning communities since it is robust when faced with heavy-tailed noise or outliers in practice.
Fan Xie +3 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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Stochastic Gradient Descent for Kernel-Based Maximum Correntropy Criterion [PDF]
EntropyMaximum correntropy criterion (MCC) has been an important method in machine learning and signal processing communities since it was successfully applied in various non-Gaussian noise scenarios.
Tiankai Li +3 more
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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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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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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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Partial maximum correntropy regression for robust electrocorticography decoding
Frontiers in Neuroscience, 2023 The Partial Least Square Regression (PLSR) method has shown admirable competence for predicting continuous variables from inter-correlated electrocorticography signals in the brain-computer interface.
Yuanhao Li +4 more
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