Results 71 to 80 of about 543 (157)

Cooperative Positioning for Multi-AUVs Based on Factor Graph and Maximum Correntropy

IEEE Access, 2019
Cooperative positioning (CP) is considered as a promising positioning method for multiple autonomous underwater vehicles (multi-AUVs), because CP is characterized by low cost and high precision.
Shiwei Fan, Ya Zhang, Qiang Hao, Pan Jiang, Chunyang Yu, Fei Yu   +5 more
doaj   +1 more source

KLMS‐Net: Deep unrolling for kernel least mean square algorithm

Electronics Letters, Volume 61, Issue 1, January/December 2025.
This letter proposes a novel network framework based on the deep unrolling of kernel least mean square (KLMS‐Net). KLMS‐Net transforms the iterative process of KLMS into the forward propagation of deep neural networks, which learn the implicit feature mappings in a model‐driven manner, providing deep neural networks with explicit interpretability ...
Yu Tang, Tingsen Zhang, Jinrong Gao, Dongjie Bi, Xifeng Li, Yongle Xie   +5 more
wiley   +1 more source

An Attention‐Guided Semi‐Supervised Model for Power Transformer Fault Diagnosis via Vibration‐Acoustic Data Fusion

IET Electric Power Applications, Volume 19, Issue 1, January/December 2025.
This paper proposes an attention‐guided semi‐supervised model for transformer fault diagnosis using vibration‐acoustic data fusion. The model employs multilevel attention and a consistency learning strategy to enhance diagnostic accuracy under limited labelled data.
Yanfei Sun, Tao Zhao, Li Gao, Yunpeng Liu   +3 more
wiley   +1 more source

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
openaire   +2 more sources

A Student's T Distribution‐Based Filter Design for SINS/GNSS With Heavy‐Tailed Noise

IET Electric Power Applications, Volume 19, Issue 1, January/December 2025.
To reduce the affection of outliers caused by heavy‐tailed noise, the noise model is constructed by the Student's T distribution rather than the Gaussian distribution, and the related probability density functions (PDF) are adaptively modelled as student's T PDFs with different DoF parameters.
Menghao Qian, Wei Chen, Ruisheng Sun
wiley   +1 more source

An adaptive combination constrained proportionate normalized maximum correntropy criterion algorithm for sparse channel estimations

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, Yingsong Li, José Carlos M. Bermudez, Xiao Han   +3 more
doaj   +1 more source

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

Robustness analysis of a maximum correntropy framework for linear regression [PDF]

Automatica, 2018
In this paper we formulate a solution of the robust linear regression problem in a general framework of correntropy maximization. Our formulation yields a unified class of estimators which includes the Gaussian and Laplacian kernel-based correntropy estimators as special cases. An analysis of the robustness properties is then provided.
openaire   +4 more sources

Generalized Maximum Correntropy Cubature Kalman Filter with Variational Bayesian for SINS/GPS Integrated Navigation Systems

Sensors
To address the degraded accuracy and poor robustness of Strapdown Inertial Navigation Systems (SINSs)/Global Positioning Systems (GPSs) integrated navigation systems under time-varying non-Gaussian measurement noises, this paper proposes a variational ...
Weisheng Ma, Bin Wei, Xi Liu
doaj   +1 more source

Robust Sparse Underwater Acoustic Channel Estimation Using a Bidirectional Proportionate Recursive Maximum Correntropy Criterion Algorithm

Entropy
Aiming at the problem that sparse channel estimation in underwater acoustic communication is susceptible to complex multipath propagation, non-Gaussian impulsive noise, and channel time variations, this paper proposes a bidirectional proportionate ...
Xiao-Chen Chen, Guan-Quan Dai, Yang Shi, Fei-Yun Wu   +3 more
doaj   +1 more source