Results 71 to 80 of about 1,489 (178)

Secure Dynamic State Estimation of WECS‐Based Networked Microgrids Against Historical Measurement Triggered DoS Attacks

IET Control Theory &Applications, Volume 19, Issue 1, January/December 2025.
This work addresses the issue of rejection delay due to DoS attacks triggered by historical measurements during the transmission of a large amount of measurement data in WECS‐based networked microgrids. We propose a novel robust SRCKF method, designated as MCC‐SRCKF, which incorporates MCC into the SRCKF structure of DSE.
Xiao Hu, Xinghua Liu, Gaoxi Xiao, Zhongmei Pan, Peng Wang   +4 more
wiley   +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

Maximum Correntropy Square-Root Cubature Kalman Filter for Non-Gaussian Measurement Noise

IEEE Access, 2020
Cubature Kalman filter (CKF) is widely used for non-linear state estimation under Gaussian noise. However, the estimation performance may degrade greatly in presence of heavy-tailed measurement noise.
Jingjing He, Changku Sun, Baoshang Zhang, Peng Wang   +3 more
doaj   +1 more source

Clustered Multitask Nonnegative Matrix Factorization for Spectral Unmixing of Hyperspectral Data

, 2019
In this paper, the new algorithm based on clustered multitask network is proposed to solve spectral unmixing problem in hyperspectral imagery. In the proposed algorithm, the clustered network is employed.
Khoshsokhan, Sara, Rajabi, Roozbeh, Zayyani, Hadi   +2 more
core   +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

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

Robust Capsule Network Based on Maximum Correntropy Criterion for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Recently, deep learning-based algorithms have been widely used for classification of hyperspectral images (HSIs) by extracting invariant and abstract features.
Heng-Chao Li, Wei-Ye Wang, Lei Pan, Wei Li, Qian Du, Ran Tao   +5 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

Robust Dynamic State Estimation of Power System With Measurement Outliers Based on Parameterized Analytical Cubature Kalman Filter

IET Renewable Power Generation, Volume 19, Issue 1, January/December 2025.
Accurate state estimation is paramount for the smooth operation and management of power systems, significantly contributing to their safety, stability, and reliability. However, the presence of channel noise and outliers stemming from phasor measurement units renders the noise model a deviation from the Gaussian distribution. To mitigate this challenge,
Mingyang Liu, Yanxin Liu, Yi Wang, Venkata Dinavahi, Ze Gao   +4 more
wiley   +1 more source

Passive Target Motion Analysis With Own‐Ship Location Uncertainty in the Presence of Non‐Gaussian Sensor Noise

IET Radar, Sonar &Navigation, Volume 19, Issue 1, January/December 2025.
This work explores underwater TMA by incorporating time delay and Doppler frequency measurements along with angle data, eliminating the need for own‐ship manoeuvre and improving estimation accuracy in presence of non‐Gaussian sensor noise. Furthermore, since the own‐ship's position is inherently uncertain due to navigation errors, this work addresses ...
Rohit Kumar Singh, Shreya Das, Shovan Bhaumik   +2 more
wiley   +1 more source