A practical introduction to EEG Time-Frequency Principal Components Analysis (TF-PCA) [PDF]
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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mbDenoise: microbiome data denoising using zero-inflated probabilistic principal components analysis [PDF]
Genome Biology, 2022 The analysis of microbiome data has several technical challenges. In particular, count matrices contain a large proportion of zeros, some of which are biological, whereas others are technical.
Yanyan Zeng +4 more
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The Modified Principal Component Analysis Feature Extraction Method for the Task of Diagnosing Chronic Lymphocytic Leukemia Type B-CLL [PDF]
Journal of Universal Computer Science, 2020 The vast majority of medical problems are characterised by the relatively high spatial dimensionality of the task, which becomes problematic for many classic pattern recognition algorithms due to the well-known phenomenon of the curse of dimensionality ...
Mariusz Topolski
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Principal components analysis of population admixture. [PDF]
PLoS ONE, 2012 With the availability of high-density genotype information, principal components analysis (PCA) is now routinely used to detect and quantify the genetic structure of populations in both population genetics and genetic epidemiology.
Jianzhong Ma, Christopher I Amos
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A genealogical interpretation of principal components analysis. [PDF]
PLoS Genetics, 2009 Principal components analysis, PCA, is a statistical method commonly used in population genetics to identify structure in the distribution of genetic variation across geographical location and ethnic background. However, while the method is often used to
Gil McVean
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The classification of concentration of mixture of analytes
Lietuvos Matematikos Rinkinys, 2004 This paper presents a system which is used for the classification of biosensor signals. The proposed system is applied to the the synthesized and experimental data. The developed system showed good prediction perfomance.
Romas Baronas +3 more
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Principal components analysis of employment in Eastern Europe [PDF]
Panoeconomicus, 2006 For the last decade, the employment structure is one of the fastest changing areas of Eastern Europe. This paper explores the best methodology to compare the employment situations in the countries of this region.
Savić Mirko
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Principal components analysis for mixtures with varying concentrations
Modern Stochastics: Theory and Applications, 2021 Principal Component Analysis (PCA) is a classical technique of dimension reduction for multivariate data. When the data are a mixture of subjects from different subpopulations one can be interested in PCA of some (or each) subpopulation separately.
Olena Sugakova, Rostyslav Maiboroda
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Power swing detecting method using principal components analysis
Energy Reports, 2021 During power swing, the distance protection is easily affected by the oscillations of voltage and current which may lead to the mal-operation of the protection. Therefore, a power swing detecting unit is needed to cooperate with distance protection.
Hao Wang +7 more
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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
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