Results 31 to 40 of about 209 (123)
Complex Correntropy Applied to a Compressive Sensing Problem in an Impulsive Noise Environment
IEEE Access, 2019 Correntropy is a similarity function capable of extracting high-order statistical information from data. It has been used in different kinds of applications as a cost function to overcome traditional methods in non-Gaussian noise environments. One of the
Joao P. F. Guimaraes +4 more
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Mathematics, 2023 This paper studies the identification for fractional-order systems (FOSs) under stable distribution noises. First, the generalized operational matrix of block pulse functions is used to convert the identified system into an algebraic one.
Yao Lu
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Entropy, 2017 A soft parameter function penalized normalized maximum correntropy criterion (SPF-NMCC) algorithm is proposed for sparse system identification. The proposed SPF-NMCC algorithm is derived on the basis of the normalized adaptive filter theory, the maximum ...
Yingsong Li +3 more
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Robust 3D point cloud registration based on bidirectional Maximum Correntropy Criterion. [PDF]
PLoS ONE, 2018 This paper presents a robust 3D point cloud registration algorithm based on bidirectional Maximum Correntropy Criterion (MCC). Comparing with traditional registration algorithm based on the mean square error (MSE), using the MCC is superior in dealing ...
Xuetao Zhang, Libo Jian, Meifeng Xu
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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 +3 more
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Robust Partial Multi‐Label Learning Under Dual Noise via Joint Subspace Learning
CAAI Transactions on Intelligence Technology, Volume 11, Issue 3, Page 754-768, June 2026.ABSTRACT Partial Multi‐label Learning (PML) deals with the ambiguity where each instance is annotated with a set of candidate labels, and only a subset of which is valid. While existing PML methods focus primarily on label disambiguation, they often rely on the assumption of a clean feature space.
Yuanjian Zhang +4 more
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IET Communications, Volume 20, Issue 1, January/December 2026.This paper addresses channel estimation in mmWave (millimetre wave) hybrid MIMO (multiple‐input multiple‐output) systems impaired by residual transceiver hardware nonidealities, modelled as additive non‐Gaussian noise via Bussgang decomposition. A hyperparameter‐free maximum Versoria criterion (MVC)‐based channel estimator is proposed, featuring a ...
Rangeet Mitra +5 more
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Electronics Letters, Volume 62, Issue 1, January/December 2026.Acoustic echo cancellation (AEC) in actual communication systems is challenging due to highly correlated inputs, impulsive disturbances, and computational limitations. The traditional Affine Projection Algorithm (APA) is better than the Normalised Least Mean Square method, although it involves matrix inversion complexity and is susceptible to outliers (
Gagandeep Singh +5 more
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IEEE Access, 2019 In this paper, a kind of active coefficient detection (ACD)-based maximum correntropy criterion (MCC) algorithm is proposed to estimate a sparse multi-path channel under the non-Gaussian environments. The proposed ACD-based MCC algorithms are realized by
Zeyang Sun +3 more
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IEEE Access, 2020 In wireless sensor networks (WSN), measurements are always corrupted by outliers or impulsive noise. Cubature information filtering (CIF) is founded based on minimum mean square error (MMSE) criterion, which is not applicable to non-Gaussian noise. Hence,
Jiahao Zhang +5 more
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