Results 91 to 100 of about 1,526 (199)

Robust Clustering and Anomaly Detection of User Electricity Consumption Behavior Based on Correntropy

IET Generation, Transmission &Distribution, Volume 19, Issue 1, January/December 2025.
This paper proposes a robust, user‐type‐specific anomaly detection method for electricity usage. First, after data cleaning and preprocessing, a correntropy‐based K‐means clustering method is proposed to perform robust clustering, effectively separating users with non‐Gaussian noisy data.
Teng Zhang, XuSheng Qian, Yu Zhou, GaoJun Xu, Ming Wu   +4 more
wiley   +1 more source

Spatial Perception Correntropy Matrix for Hyperspectral Image Classification

, 2022
With the development of the hyperspectral imaging technique, hyperspectral image (HSI) classification is receiving more and more attention. However, due to high dimensionality, limited or unbalanced training samples, spectral variability, and mixing ...
Weijia Cao, Guochao Zhang, Yantao Wei
core   +1 more source

Kernel Adaptive Filters With Feedback Based on Maximum Correntropy

, 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, Chi K. Tse, Wanli Wang, Guobing Qian, Lujuan Dang   +4 more
core   +1 more source

A Simplified DOA Estimation Method Based on Correntropy in the Presence of Impulsive Noise

IEEE Access, 2018
Many approaches have been studied in the field of array signal processing when impulsive noise is modeled with an alpha-stable distribution. By introducing the correntropy, which exhibits a robust statistics property, this paper defines a correntropy ...
Quan Tian, Tianshuang Qiu, Jitong Ma, Jingchun Li, Rong Li   +4 more
doaj   +1 more source

Probabilistic Interpretation for Correntropy with Complex Data

CoRR, 2016
5 pages, 2 ...
João P. F. Guimarães, Aluisio I. Rêgo Fontes, Joilson B. A. Rego, Allan de M. Martins   +3 more
openaire   +2 more sources

Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning

IEEE Access, 2019
This paper proposes a topological clustering algorithm by integrating topological structure and information theoretic learning, i.e., correntropy, into adaptive resonance theory (ART). Specifically, the proposed algorithm utilizes the correntropy induced
Naoki Masuyama, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota, Yusuke Nojima, Yiping Liu   +5 more
doaj   +1 more source

Complex Correntropy: Probabilistic Interpretation and Optimization

CoRR, 2016
arXiv admin note: substantial text overlap with arXiv:1606 ...
openaire   +2 more sources

A Quantized Kernel Learning Algorithm Using a Minimum Kernel Risk-Sensitive Loss Criterion and Bilateral Gradient Technique

Entropy, 2017
Recently, inspired by correntropy, kernel risk-sensitive loss (KRSL) has emerged as a novel nonlinear similarity measure defined in kernel space, which achieves a better computing performance.
Xiong Luo, Jing Deng, Weiping Wang, Jenq-Haur Wang, Wenbing Zhao   +4 more
doaj   +1 more source

Robust tensor factorization using maximum correntropy criterion

, 2016
Traditional tensor decomposition methods, e.g., two dimensional principle component analysis (2DPCA) and two dimensional singular value decomposition (2DSVD), minimize mean square errors (MSE) and are sensitive to outliers.
La Salle, John, Gao, Y, Liang, J, Sun, Changming, Zhang, Lena, Sun, C, Zhang, M, Liang, Junli, La Salle, J, Gao, Yongsheng   +9 more
core   +1 more source

Rolling Element Bearing Fault Diagnosis under Impulsive Noise Environment Based on Cyclic Correntropy Spectrum

Entropy, 2019
Rolling element bearings are widely used in various industrial machines. Fault diagnosis of rolling element bearings is a necessary tool to prevent any unexpected accidents and improve industrial efficiency.
Xuejun Zhao, Yong Qin, Changbo He, Limin Jia, Linlin Kou   +4 more
doaj   +1 more source