Sentence examples for identification of principal components from inspiring English sources
Aiming at reducing the complexity, we developed novel reduced-rank identification of principal components (RIPC) algorithms.
This derivation naturally leads to identification of principal components of the energy flux through an arbitrary cross-section of a shell and to formulation of Green's matrix for an infinitely long shell at each individual circumferential wave number.
In Principal Component Analysis (PCA) this new coordinate system is used to compute the so-called population of principal components.
Correlation of principal components versus different confounders.
In this study, we are interested in not only the first principal components but also the other principal components, as well as quadratics and interactions of principal components.
Identification of subsidiary principal components required the selective elimination of correlations between probes and a previously identified PC variable.
A suitable definition of a neighbourhood is points lying within a distance of 1.2 cm of prom, as this provided around 65 points on average, to ensure stable identification of the principal components.
This approach enabled identification of several factors associated directly with clusters of principal component scores.
The study confirmed the validity of the use of mathematical techniques of principal component analysis (PCA) and hierarchical cluster analysis (HCA) for source identification and principal component analysis/absolute principal component scores (PCA/APCS) receptor model for pollutant load quantification.
Identification and quantification of illicit drugs is accomplished on these substrates with the aid of Principal Component Analysis (PCA) coupled with a Support Vector Machine (SVM).
Differentiation was improved with the use of principal component analysis (PCA), a powerful statistical tool that allows the identification of patterns in any dataset and highlights their similarities and differences.
