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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Maximum Correntropy Criterion With Variable Center [PDF]
IEEE Signal Processing Letters, 2019 5 pages, 1 ...
Badong Chen +3 more
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Electricity Consumption Forecasting Scheme via Improved LSSVM with Maximum Correntropy Criterion [PDF]
Entropy, 2018 In recent years, with the deepening of China’s electricity sales side reform and electricity market opening up gradually, the forecasting of electricity consumption (FoEC) becomes an extremely important technique for the electricity market.
Jiandong Duan +4 more
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Robust 3D point cloud registration based on bidirectional Maximum Correntropy Criterion. [PDF]
PLoS ONE, 2018 This paper presents a robust 3D point cloud registration algorithm based on bidirectional Maximum Correntropy Criterion (MCC). Comparing with traditional registration algorithm based on the mean square error (MSE), using the MCC is superior in dealing ...
Xuetao Zhang, Libo Jian, Meifeng Xu
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Maximum Correntropy Criterion Kalman/Allan Variance-Assisted FIR Integrated Filter for Indoor Localization [PDF]
MicromachinesTo obtain more accurate information on using an inertial navigation system (INS)-based integrated localization system, an integrated filter with maximum correntropy criterion Kalman filter (mccKF) and finite impulse response (FIR) is proposed for the ...
Manman Li +4 more
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Adaptive Robust Unscented Kalman Filter via Fading Factor and Maximum Correntropy Criterion [PDF]
Sensors, 2018 In most practical applications, the tracking process needs to update the data constantly. However, outliers may occur frequently in the process of sensors’ data collection and sending, which affects the performance of the system state estimate.
Zhihong Deng +3 more
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2D and 3D Angles-Only Target Tracking Based on Maximum Correntropy Kalman Filters [PDF]
Sensors, 2022 In this paper, angles-only target tracking (AoT) problem is investigated in the non Gaussian environment. Since the conventional minimum mean square error criterion based estimators tend to give poor accuracy in the presence of large outliers or ...
Asfia Urooj +3 more
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Variational Bayesian-Based Improved Maximum Mixture Correntropy Kalman Filter for Non-Gaussian Noise [PDF]
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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Robust deep network with maximum correntropy criterion for seizure detection. [PDF]
Biomed Res Int, 2014 Effective seizure detection from long-term EEG is highly important for seizure diagnosis. Existing methods usually design the feature and classifier individually, while little work has been done for the simultaneous optimization of the two parts. This work proposes a deep network to jointly learn a feature and a classifier so that they could help each ...
Qi Y, Wang Y, Zhang J, Zhu J, Zheng X.
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Robust Motion Averaging under Maximum Correntropy Criterion [PDF]
2021 IEEE International Conference on Robotics and Automation (ICRA), 2021 Recently, the motion averaging method has been introduced as an effective means to solve the multi-view registration problem. This method aims to recover global motions from a set of relative motions, where the original method is sensitive to outliers due to using the Frobenius norm error in the optimization.
Jihua Zhu +5 more
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