Results 31 to 40 of about 5,059,929 (339)
Generalized Correntropy for Robust Adaptive Filtering [PDF]
IEEE Transactions on Signal Processing, 2015 As a robust nonlinear similarity measure in kernel space, correntropy has received increasing attention in domains of machine learning and signal processing. In particular, the maximum correntropy criterion (MCC) has recently been successfully applied in
Badong Chen +4 more
semanticscholar +1 more source
Hybrid Adaptive Cubature Kalman Filter with Unknown Variance of Measurement Noise
Sensors, 2018 This paper is concerned with the filtering problem caused by the inaccuracy variance of measurement noise in real nonlinear systems. A novel weighted fusion estimation method of multiple different variance estimators is presented to estimate the variance
Yuepeng Shi +4 more
doaj +1 more source
Scientific Reports, 2022 The adaptive block size processing method in different image areas makes block-matching and 3D-filtering (BM3D) have a very good image denoising effect. Based on these observation, in this paper, we improve BM3D in three aspects: adaptive noise variance ...
Hongbin Jia, Qingbo Yin, Mingyu Lu
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Single-Stage Adaptive Multi-Scale Point Cloud Noise Filtering Algorithm Based on Feature Information
Remote Sensing, 2022 This paper proposes a single-stage adaptive multi-scale noise filtering algorithm for point clouds, based on feature information, which aims to mitigate the fact that the current laser point cloud noise filtering algorithm has difficulty quickly ...
Zhen Zheng +5 more
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Sensors, 2010 In this paper, the fast least-mean-squares (LMS) algorithm was used to both eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications, and improve the convergence rate of the filtering ...
Eduardo Fernández +3 more
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An Alignment Method Based on KF-ASMUKF Hybrid Filtering for Ship’s SINS under Mooring Conditions
Sensors, 2021 To solve the problem that the ship’s strapdown inertial navigation system (SINS) alignment accuracy decreases with the increase of the nonlinear filtering state dimension under mooring conditions, a method based on Kalman filter (KF) and Adaptive scale ...
Pengchao Yao, Gongliu Yang, Xiafu Peng
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Motion-Artifact Reduction in Capacitive Heart-Rate Measurements by Adaptive Filtering
IEEE Transactions on Instrumentation and Measurement, 2019 Electrocardiography (ECG) measurements are esse- ntial components in clinical diagnosis and monitoring. Conventional ECG measurements produce discomfort to the patients due to the use of gel and direct skin contact.
Lin Xu +5 more
semanticscholar +1 more source
Kernel Risk-Sensitive Loss: Definition, Properties and Application to Robust Adaptive Filtering [PDF]
IEEE Transactions on Signal Processing, 2016 Nonlinear similarity measures defined in kernel space, such as correntropy, can extract higher order statistics of data and offer potentially significant performance improvement over their linear counterparts especially in non Gaussian signal processing ...
Badong Chen +5 more
semanticscholar +1 more source
Adaptive-FRESH Filtering [PDF]
, 2011 Adaptive filters are self-designing systems for information extraction which rely for their operation on a recursive algorithm (Haykin, 2001). They find application in environments where the optimum filter cannot be applied because of lack of knowledge about the signal characteristics and/or the data to be processed.
Ojeda, Omar A. Yeste, Grajal, Jesús
openaire +3 more sources
A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation
Sensors, 2016 The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of ...
Chen Jiang, Shu-Bi Zhang, Qiu-Zhao Zhang
doaj +1 more source