Results 1 to 10 of about 150,011 (287)
Independent Component Analysis (ICA) based-clustering of temporal RNA-seq data. [PDF]
PLoS ONE, 2017 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]
SensorsThis 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]
Frontiers in Neuroinformatics, 2021 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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Comparing the reliability of different ICA algorithms for fMRI analysis.
PLoS ONE, 2022 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]
Talanta, 2020 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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Applied Sciences, 2021 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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An Over-Complete Independent Component Analysis (ICA) Approach to Magnetic Resonance Image Analysis [PDF]
2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005 This paper presents a new application of independent component analysis (ICA) in magnetic resonance (MR) image analysis. One of most successful applications for ICA-based approaches in MR imaging is functional MRI (fMRI) which basically deals with one-dimensional temporal signals.
Jing, Wang +5 more
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Frontiers in Human Neuroscience, 2013 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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Independent component analysis: An introduction [PDF]
Applied Computing and Informatics, 2021 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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Comparison of dimension reduction methods on fatty acids food source study
Scientific Reports, 2021 Serum fatty acids (FAs) exist in the four lipid fractions of triglycerides (TGs), phospholipids (PLs), cholesteryl esters (CEs) and free fatty acids (FFAs). Total fatty acids (TFAs) indicate the sum of FAs in them.
Yifan Chen +15 more
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