Results 11 to 20 of about 5,059,929 (339)
Robust adaptive filtering algorithms based on (inverse)hyperbolic sine function. [PDF]
PLoS ONE, 2021 Recently, adaptive filtering algorithms were designed using hyperbolic functions, such as hyperbolic cosine and tangent function. However, most of those algorithms have few parameters that need to be set, and the adaptive estimation accuracy and ...
Sihai Guan +3 more
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IEEE Transactions on Cybernetics, 2019 This paper focuses on the issue of designing an adaptive event-triggered scheme to the decentralized filtering for a class of networked nonlinear interconnected system.
Z. Gu, P. Shi, D. Yue, Z. Ding
semanticscholar +3 more sources
Positivity-Preserving Entropy-Based Adaptive Filtering for Discontinuous Spectral Element Methods [PDF]
Journal of Computational Physics, 2022 In this work, we present a positivity-preserving entropy-based adaptive filtering method for shock capturing in discontinuous spectral element methods. By adapting the filter strength to enforce positivity and a local discrete minimum entropy principle ...
T. Dzanic, F. Witherden
semanticscholar +1 more source
Improving the Efficiency of Electric Rolling Stock Operation Through the Use of Adaptive Filtering Methods for High Harmonic Current Components in Traction Drive Systems [PDF]
Problems of the Regional Energetics, 2023 The aim of this work is to investigate the efficiency of various adaptive filtering methods for higher harmonic components of stator currents in a vector-controlled traction drive system to improve the operation efficiency of electric rolling stock.
Goolak S.
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An approach to adaptive filtering with variable step size based on geometric algebra
IET Communications, 2022 Recently, adaptive filtering algorithms have attracted much more attention in the field of signal processing. By studying the shortcoming of the traditional real‐valued fixed step size adaptive filtering algorithm, this paper proposed the novel approach ...
Haiquan Wang +3 more
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Boosted adaptive filters [PDF]
Digital Signal Processing, 2018 Abstract We introduce the boosting notion of machine learning to the adaptive signal processing literature. In our framework, we have several adaptive filtering algorithms, i.e., the weak learners, that run in parallel on a common task such as equalization, classification, regression or filtering.
Kari, Dariush +4 more
openaire +4 more sources
ACM Journal of Experimental Algorithmics, 2018 We introduce the adaptive cuckoo filter (ACF), a data structure for approximate set membership that extends cuckoo filters by reacting to false positives, removing them for future queries. As an example application, in packet processing queries may correspond to flow identifiers, so a search for an element is likely to be followed by repeated searches ...
Mitzenmacher M +2 more
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Adaptive Filtering Revisited [PDF]
Journal of the Operational Research Society, 1979 This paper shows that the adaptive filtering and forecasting techniques proposed by Makridakis and Wheelwright can be viewed as approximations to a more precise filtering method in which the Kalman filter is applied to a dynamic autoregressive model which is a special case of the models of Harrison and Stevens.
Nau, Robert F, Oliver, Robert M
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Asymmetric Correntropy for Robust Adaptive Filtering [PDF]
IEEE Transactions on Circuits and Systems - II - Express Briefs, 2019 In recent years, correntropy has been successfully applied to robust adaptive filtering to eliminate adverse effects of impulsive noises or outliers. Correntropy is generally defined as the expectation of a Gaussian kernel between two random variables ...
Badong Chen +4 more
semanticscholar +1 more source
Mesh Denoising via Adaptive Consistent Neighborhood
Sensors, 2021 In this paper, we propose a novel guided normal filtering followed by vertex updating for mesh denoising. We introduce a two-stage scheme to construct adaptive consistent neighborhoods for guided normal filtering.
Mingqiang Guo +5 more
doaj +1 more source