Results 71 to 80 of about 708 (167)
Robust Maximum Correntropy Kalman Filter
International Journal of Robust and Nonlinear ControlABSTRACTThe Kalman filter provides an optimal estimation for a linear system with Gaussian noise. However, when the noises are non‐Gaussian in nature, its performance deteriorates rapidly. For non‐Gaussian noises, maximum correntropy Kalman filter (MCKF) is developed which provides a more accurate result.
Joydeb Saha, Shovan Bhaumik
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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 +5 more
wiley +1 more source
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 +3 more
wiley +1 more source
Kernel Mixture Correntropy Conjugate Gradient Algorithm for Time Series Prediction
Entropy, 2019 Kernel adaptive filtering (KAF) is an effective nonlinear learning algorithm, which has been widely used in time series prediction. The traditional KAF is based on the stochastic gradient descent (SGD) method, which has slow convergence speed and low ...
Nan Xue +6 more
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Sensors, 2018 This paper considers the parameter estimation problem under non-stationary environments in sensor networks. The unknown parameter vector is considered to be a time-varying sequence.
Limei Hu +3 more
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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 +4 more
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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 +5 more
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Probabilistic Interpretation for Correntropy with Complex Data
CoRR, 2016 5 pages, 2 ...
João P. F. Guimarães +3 more
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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 +4 more
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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 +4 more
doaj +1 more source