Results 1 to 10 of about 935 (185)
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.
Xi Liu, Badong Chen, Paul Honeine
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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.
Jim Jing-Yan Wang +2 more
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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 Kernel-Width Adaption Diffusion Maximum Correntropy Algorithm [PDF]
IEEE Access, 2020 Impulsive noises are widely existing in various systems like noise cancellation system and wireless communication systems, where adaptive filtering (AF) is always employed to identify specific systems.
Ying Guo, Bing Ma, Yingsong Li
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Remote Sensing, 2022 To improve the accuracy of the maximum correntropy Kalman filter (MCKF) in wireless sensors networks (WSNs) positioning, a dynamic self-tuning maximum correntropy Kalman filter (DSTMCKF) is proposed, where innovation and the sensors information of the ...
Tianrui Liao +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.
Badong Chen, Xi Liu, Haiquan Zhao
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Maximum Correntropy Criterion With Variable Center [PDF]
IEEE Signal Processing Letters, 2019 5 pages, 1 ...
Badong Chen, Xin Wang, Yingsong Li
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Maximum Correntropy Kalman Filter With State Constraints
IEEE Access, 2017 For linear systems, the original Kalman filter under the minimum mean square error (MMSE) criterion is an optimal filter under a Gaussian assumption. However, when the signals follow non-Gaussian distributions, the performance of this filter deteriorates
Xi Liu +4 more
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Maximum Total Improper Complex Correntropy Algorithm for Widely Linear Adaptive Filtering
IEEE Access, 2022 The maximum total complex correntropy (MTCC) algorithm improves the performance of adaptive filtering under the error in variable (EIV) model by integrating both input and output noise information into the total complex correntropy.
Lianqing Fu, Li Zhou
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Generalized Asymmetric Correntropy for Robust Adaptive Filtering: A Theoretical and Simulation Study
Remote Sensing, 2022 Correntropy has been proved to be effective in eliminating the adverse effects of impulsive noises in adaptive filtering. However, correntropy is not desirable when the error between the two random variables is asymmetrically distributed around zero.
Hua Qu +5 more
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