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A practical introduction to EEG Time-Frequency Principal Components Analysis (TF-PCA)
Developmental Cognitive Neuroscience, 2022 This EEG methods tutorial provides both a conceptual and practical introduction to a promising data reduction approach for time-frequency representations of EEG data: Time-Frequency Principal Components Analysis (TF-PCA).
George A. Buzzell +3 more
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PCA of PCA: principal component analysis of partial covering absorption in NGC 1365 [PDF]
Monthly Notices of the Royal Astronomical Society, 2014 We analyse 400 ks of XMM-Newton data on the active galactic nucleus NGC 1365 using principal component analysis (PCA) to identify model independent spectral components. We find two significant components and demonstrate that they are qualitatively different from those found in MCG?6-30-15 using the same method.
Parker, M. L. +3 more
openaire +7 more sources
Application of Principal Component Analysis for Steel Material Components
Kurdistan Journal of Applied Research, 2022 In this research, we made use of the principal component analysis (PCA) technique, which is a multivariate statistical method that transforms a fixed number of correlated variables into a fixed number of orthogonal, uncorrelated axes known as principal ...
Miran Othman Tofiq +1 more
doaj +3 more sources
Remote Sensing, 2022 Recently, Jia et al. employed the index, modified remote sensing ecological index (MRSEI), to evaluate the ecological quality of the Qaidam Basin, China. The MRSEI made a modification to the previous remote sensing-based ecological index (RSEI), which is
Hanqiu Xu +3 more
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Adaptive dimensionality reduction for neural network-based online principal component analysis.
PLoS ONE, 2021 "Principal Component Analysis" (PCA) is an established linear technique for dimensionality reduction. It performs an orthonormal transformation to replace possibly correlated variables with a smaller set of linearly independent variables, the so-called ...
Nico Migenda +2 more
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ANOVA bootstrapped principal components analysis for logistic regression
Croatian Review of Economic, Business and Social Statistics, 2022 Principal components analysis (PCA) is often used as a dimensionality reduction technique. A small number of principal components is selected to be used in a classification or a regression model to boost accuracy.
Toleva Borislava
doaj +1 more source
Online Commerce Pattern in European Union Countries between 2019 and 2020
Societies, 2022 The development of information technology, along with the high growth and diversification of consumer needs, has revolutionized the way in which business-to-consumer transactions occur.
Cristina Burlacioiu
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Chemometric approach to evaluate heavy metals’ content in Daucus Carota from different localities in Serbia [PDF]
Hemijska Industrija, 2015 The aim of this study was to evaluate heavy metal content in carrots (Daucus carota) from the different localities in Serbia and assess by the cluster analysis (CA) and principal components analysis (PCA) the heavy metal contamination of carrots
Mitic Violeta D. +6 more
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Optimized Principal Component Analysis on Coronagraphic Images of the Fomalhaut System [PDF]
, 2013 We present the results of a study to optimize the principal component analysis (PCA) algorithm for planet detection, a new algorithm complementing ADI and LOCI for increasing the contrast achievable next to a bright star.
Amara, A. +3 more
core +3 more sources
Construction of Air Quality Level Prediction Model Based on STEPDISC-PCA-BP
Applied Sciences, 2023 Air quality level has a complex nonlinear relationship with air pollutant and meteorological conditions, including multiple factors, overlapping information, and difficulty solving equations. In order to identify significant factors, remove correlations,
Min Liu +4 more
doaj +1 more source