Results 21 to 30 of about 935 (185)
Variational Bayesian-Based Improved Maximum Mixture Correntropy Kalman Filter for Non-Gaussian Noise
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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Generalized Maximum Complex Correntropy Augmented Adaptive IIR Filtering
Entropy, 2022 Augmented IIR filter adaptive algorithms have been considered in many studies, which are suitable for proper and improper complex-valued signals. However, lots of augmented IIR filter adaptive algorithms are developed under the mean square error (MSE ...
Haotian Zheng, Guobing Qian
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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 Ensemble Kalman Filter
2023 62nd IEEE Conference on Decision and Control (CDC), 2023 Accepted by 62nd IEEE Conference on Decision and Control (CDC 2023)
Yangtianze Tao +2 more
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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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Robust Pose Estimation Based on Maximum Correntropy Criterion
, 2021 Pose estimation is a key problem in computer vision, which is commonly used in augmented reality, robotics and navigation. The classical orthogonal iterative (OI) pose estimation algorithm builds its cost function based on the minimum mean square error (MMSE), which performs well when data disturbed by Gaussian noise.
Qian Zhang, Badong Chen
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Adaptive Maximum Correntropy Gaussian Filter Based on Variational Bayes [PDF]
Sensors, 2018 In this paper, we investigate the state estimation of systems with unknown covariance non-Gaussian measurement noise. A novel improved Gaussian filter (GF) is proposed, where the maximum correntropy criterion (MCC) is used to suppress the pollution of ...
Guoqing Wang +3 more
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Information, 2023 This paper addresses the multi-sensor fusion target tracking problem based on maximum mixture correntropy in non-Gaussian noise environments exclusively using Doppler measurements.
Changyu Yi, Minzhe Li, Shuyi Li
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Robust Hammerstein Adaptive Filtering under Maximum Correntropy Criterion
Entropy, 2015 The maximum correntropy criterion (MCC) has recently been successfully applied to adaptive filtering. Adaptive algorithms under MCC show strong robustness against large outliers.
Zongze Wu +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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