Results 21 to 30 of about 705 (186)
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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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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EURASIP Journal on Advances in Signal Processing, 2018 An adaptive combination constrained proportionate normalized maximum correntropy criterion (ACC-PNMCC) algorithm is proposed for sparse multi-path channel estimation under mixed Gaussian noise environment. The developed ACC-PNMCC algorithm is implemented
Yanyan Wang +3 more
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Adaptive Filtering Under the Maximum Correntropy Criterion With Variable Center [PDF]
IEEE Access, 2019 Recently, an extended version of correntropy, whose center can locate at any position has been proposed and applied in a new optimization criterion called maximum correntropy criterion with variable center (MCC-VC).
Lingfei Zhu +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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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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Learning with the maximum correntropy criterion induced losses for regression.
J. Mach. Learn. Res., 2015 sponsorship: EU: The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC AdG A-DATADRIVE-B (290923). This paper reflects only the authors' views, the Union is not liable for any use that may be made of the contained information.
Feng, Yunlong +4 more
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A Robust GPS Navigation Filter Based on Maximum Correntropy Criterion with Adaptive Kernel Bandwidth. [PDF]
Sensors (Basel), 2023 Multiple forms of interference and noise that impact the receiver’s capacity to receive and interpret satellite signals, and consequently the preciseness of positioning and navigation, may be present during the processing of Global Positioning ...
Jwo DJ, Chen YL, Cho TS, Biswal A.
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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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KPCA Based Novelty Detection Method Using Maximum Correntropy Criterion [PDF]
Jisuanji kexue, 2022 Novelty detection is an important research issue in the field of machine learning.Till now,there exist lots of novelty detection approaches.As a commonly used kernel method,kernel principal component analysis(KPCA)has been successfully applied to deal ...
LI Qi-ye, XING Hong-jie
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