Results 21 to 30 of about 209 (123)

Maximum Correntropy Criterion with Distributed Method

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, Ting Hu, Shixu Wang, Baobin Wang   +3 more
doaj   +1 more source

Aircraft trajectory filtering method based on Gaussian‐sum and maximum correntropy square‐root cubature Kalman filter

Cognitive Computation and Systems, Volume 4, Issue 3, Page 205-217, September 2022., 2022
Abstract Aiming at meetiing the need to filtering flight trajectory data for aircraft testing, a novel adaptive cubature Kalman filter (CKF) is proposed based on the maximum correntropy and Gaussian‐sum in this paper. Firstly, based on the traditional CKF algorithm, we introduced a Gaussian‐sum method to approximate non‐Gaussian noise to get more ...
Jing G. Bai, Quan B. Ge, Hong Li, Jian M. Xiao, Yuan L. Wang   +4 more
wiley   +1 more source

Kernel Adaptive Filters With Feedback Based on Maximum Correntropy

IEEE Access, 2018
This paper presents novel kernel adaptive filters with feedback, namely, kernel recursive maximum correntropy with multiple feedback (KRMC-MF) and its simplified version, a linear recurrent kernel online learning algorithm based on maximum correntropy ...
Shiyuan Wang, Lujuan Dang, Wanli Wang, Guobing Qian, Chi K. Tse   +4 more
doaj   +1 more source

A robust spatio‐temporal prediction approach for wind power generation based on spectral temporal graph neural network

IET Renewable Power Generation, Volume 16, Issue 12, Page 2556-2565, 7 September 2022., 2022
Abstract At present, the penetration of wind power generation is increasing remarkably worldwide, and the accurate wind power forecasting (WPF) is essential to ensure the reliability and economy of the power system. Most of the current work of WPF only capture temporal correlation in the time domain but ignore the spatial correlation.
Yuqin He, Songjian Chai, Jian Zhao, Yuxin Sun, Xian Zhang   +4 more
wiley   +1 more source

An approach to adaptive filtering with variable step size based on geometric algebra

IET Communications, Volume 16, Issue 10, Page 1094-1105, 23 June 2022., 2022
Abstract Recently, adaptive filtering algorithms have attracted much more attention in the field of signal processing. By studying the shortcoming of the traditional real‐valued fixed step size adaptive filtering algorithm, this paper proposed the novel approach to adaptive filtering with variable step size based on Sigmoid function and geometric ...
Haiquan Wang, Yinmei He, Yanping Li, Rui Wang   +3 more
wiley   +1 more source

Interacting Multiple Model Filter with a Maximum Correntropy Criterion for GPS Navigation Processing

Applied Sciences, 2023
In order to deal with the uncertainty of measurement noise, particularly for outlier types of multipath interference and non-line of sight (NLOS) reception, this paper proposes a novel method for processing the navigation states of the Global Positioning
Dah-Jing Jwo, Jen-Hsien Lai, Yi Chang
doaj   +1 more source

Multi-Sensor Integrated Navigation Fusion Algorithm Based on Maximum Correntropy Criterion [PDF]

Hangkong bingqi
Aiming at the decreasing problem that the filtering accuracy of traditional multi-sensor integrated navigation system information fusion method under non-Gaussian measurement noise， this paper extends Kalman filter based on maximum correntropy criterion （
Lin Xueyuan, Pan Xinlong, Li Xin
doaj   +1 more source

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, Badong Chen, Haiquan Zhao, Jing Qin, Jiuwen Cao   +4 more
doaj   +1 more source

Adaptive Filtering Under the Maximum Correntropy Criterion With Variable Center

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, Chengtian Song, Lizhi Pan, Jili Li   +3 more
doaj   +1 more source

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, Siyuan Peng, Badong Chen, Haiquan Zhao   +3 more
doaj   +1 more source