Results 1 to 10 of about 32,603 (155)
Independent Component Analysis (ICA) based-clustering of temporal RNA-seq data. [PDF]
Gene expression time series (GETS) analysis aims to characterize sets of genes according to their longitudinal patterns of expression. Due to the large number of genes evaluated in GETS analysis, an useful strategy to summarize biological functional ...
Moysés Nascimento +8 more
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Vibration-Based Diagnostics of Rolling Element Bearings Using the Independent Component Analysis (ICA) Method [PDF]
This manuscript presents a study on the application of blind source separation (BSS) techniques, specifically the Independent Component Analysis (ICA) method, for the detection and identification of localized faults in rolling element bearings.
Dariusz Mika +2 more
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NIRS-ICA: A MATLAB Toolbox for Independent Component Analysis Applied in fNIRS Studies [PDF]
Independent component analysis (ICA) is a multivariate approach that has been widely used in analyzing brain imaging data. In the field of functional near-infrared spectroscopy (fNIRS), its promising effectiveness has been shown in both removing noise ...
Yang Zhao +5 more
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Independent component analysis: An introduction [PDF]
Independent component analysis (ICA) is a widely-used blind source separation technique. ICA has been applied to many applications. ICA is usually utilized as a black box, without understanding its internal details.
Alaa Tharwat
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Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms [PDF]
Pk Douglas +2 more
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Comparing the reliability of different ICA algorithms for fMRI analysis.
Independent component analysis (ICA) has been shown to be a powerful blind source separation technique for analyzing functional magnetic resonance imaging (fMRI) data sets.
Pengxu Wei, Ruixue Bao, Yubo Fan
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Independent components analysis (ICA) at the “cocktail-party” in analytical chemistry [PDF]
Independent components analysis (ICA) is a probabilistic method, whose goal is to extract underlying component signals, that are maximally independent and non-Gaussian, from mixed observed signals. Since the data acquired in many applications in analytical chemistry are mixtures of component signals, such a method is of great interest.
Monakhova, Yulia, Rutledge, Douglas
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Dimensional reduction methods have significantly improved the simplification of Pulsed Thermography (PT) data while improving the accuracy of the results. Such approaches reduce the quantity of data to analyze and improve the contrast of the main defects
Julien R. Fleuret +3 more
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In functional MRI it is desirable for the blood-oxygenation level dependent (BOLD) signal to be localized to the tissue containing activated neurons rather than the veins draining that tissue. This study addresses the dependence of the specificity of the
Alexander eGeissler +12 more
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Signal of interest (SOI) extraction is a vital issue in communication signal processing. In this paper, we propose two novel iterative algorithms for extracting SOIs from instantaneous mixtures, which explores the spatial constraint corresponding to the ...
Yiyu Zhou, Zhitao Huang, Xiang Wang
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