Results 141 to 150 of about 50,949 (199)

Robust principal curves based on maximum correntropy criterion

2013 International Conference on Machine Learning and Cybernetics, 2013
Principal curves are curves which pass throught the ’middle’ of a data cloud. They are sensitive to variances of data clouds. In this paper, we propose a robust principal curve model Correntropy based Principal Curve (CPC) model, based on maximum correntropy criterion (MCC).
Chun-Guo Li, Bao-Gang Hu
openaire   +1 more source

Recursive Constrained Maximum Correntropy Criterion Algorithm for Adaptive Filtering

IEEE Transactions on Circuits and Systems II: Express Briefs, 2020
Recently, the gradient based constrained maximum correntropy criterion (GCMCC) algorithm has received considerable attention since it provides superior performance to the traditional methods and is robust to the non-Gaussian noise. However, the convergence of GCMCC algorithm depends on the learning rate. With a large learning rate, GCMCC converges fast
Guobing Qian, Xiaohan Ning, Shiyuan Wang
openaire   +1 more source

Maximum-Correntropy-Criterion-Based Extended Kalman Filter for Ultrawideband Distance Data Fusion Under Colored Measurement Noise

IEEE Sensors Journal
This article proposes a maximum-correntropy-criterion (MCC)-based extended Kalman filter (EKF) assisted by a finite impulse response (FIR) filter to mitigate the impact of colored measurement noise (CMN) on the accuracy of fused ultrawideband (UWB ...
Yuan Xu, Xiyuan Chen, Chong Shen, Maoxiang Zhou, XiangPeng Wang   +4 more
semanticscholar   +1 more source

Robust Multidimensional Scaling Using a Maximum Correntropy Criterion

IEEE Transactions on Signal Processing, 2017
Multidimensional scaling (MDS) refers to a class of dimensionality reduction techniques, which represent entities as points in a low-dimensional space so that the interpoint distances approximate the initial pairwise dissimilarities between entities as closely as possible. The traditional methods for solving MDS are susceptible to outliers.
Fotios D. Mandanas, Costas Kotropoulos
openaire   +1 more source

Robust Principal Component Analysis Based on Maximum Correntropy Criterion

IEEE Transactions on Image Processing, 2011
Principal component analysis (PCA) minimizes the mean square error (MSE) and is sensitive to outliers. In this paper, we present a new rotational-invariant PCA based on maximum correntropy criterion (MCC). A half-quadratic optimization algorithm is adopted to compute the correntropy objective.
Ran He 0001, Bao-Gang Hu, Wei-Shi Zheng 0001, Xiangwei Kong 0001   +3 more
openaire   +2 more sources

Maximum Correntropy Criterion-Based Hierarchical One-Class Classification

IEEE Transactions on Neural Networks and Learning Systems, 2021
Due to the effectiveness of anomaly/outlier detection, one-class algorithms have been extensively studied in the past. The representatives include the shallow-structure methods and deep networks, such as the one-class support vector machine (OC-SVM), one-class extreme learning machine (OC-ELM), deep support vector data description (Deep SVDD), and ...
Jiuwen Cao, Haozhen Dai, Baiying Lei, Chun Yin, Huanqiang Zeng, Anton Kummert   +5 more
openaire   +2 more sources

Maximum Correntropy Criterion-Newton Algorithm for Adaptive Interpolated Volterra Filter

IEEE Transactions on Instrumentation and Measurement
The main drawback of the second-order Volterra (SOV) filter is that its coefficients increase exponentially with the length of the memory, which has promoted the development of sparse-interpolated Volterra filters.
Tao Deng, Lu Lu, Guangya Zhu
semanticscholar   +1 more source

A Variable Parameter LMS Algorithm Based on Generalized Maximum Correntropy Criterion for Graph Signal Processing

IEEE Transactions on Signal and Information Processing over Networks, 2023
The least mean square (LMS) algorithm of the graph signal processing (GSP) based on the mean square error criterion has a poor reconstruction effect when the graph sampling signal is disturbed by impulse noise.
Haiquan Zhao, Wang Xiang, Shaohui Lv
semanticscholar   +1 more source

Maximum Correntropy Criterion Constrained Kalman Filter

Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications, 2017
Non-Gaussian noise may degrade the performance of the Kalman filter because the Kalman filter uses only second-order statistical information, so it is not optimal in non-Gaussian noise environments. Also, many systems include equality or inequality state constraints that are not directly included in the system model, and thus are not incorporated in ...
Seyed Fakoorian, Mahmoud Moosavi, Reza Izanloo, Vahid Azimi, Dan Simon   +4 more
openaire   +1 more source

Vehicle lateral state estimation with square root cubature Kalman filter under maximum correntropy criterion

Proceedings of the Institution of mechanical engineers. Part D, journal of automobile engineering
In vehicle lateral stability control, accurately estimating the vehicle’s lateral state is crucial. Vehicle state estimation is influenced by model accuracy, filter algorithms, and sensor accuracy, which are typically assumed to be affected by Gaussian ...
Shaoyi Bei, Haoran Tang, Bo Li, Guodong Yin, Walid Daoud, Aibin Yi   +5 more
semanticscholar   +1 more source