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An improved ECG-derived respiration method using kernel principal component analysis
Recent studies show that principal component analysis (PCA) of heart beats generates well-performing ECG-derived respiratory signals (EDR). This study aims at improving the performance of EDR signals using kernel PCA (kPCA). ...
Substituent effects on H-1 and C-13 NMR chemical shifts in alpha-monosubstituted phenyl acetates by principal component analysis (PCA)
(Elsevier Science BvAmsterdamHolanda, 2005)
Support vector machine ensembles for discriminant analysis for ranking principal components
(2020-07-05)
The problem of ranking linear subspaces in principal component analysis (PCA), for multiclass classification tasks, has been addressed by building support vector machine (SVM) ensembles and AdaBoost.M2 technique. This ...
Magnitude modelling of HRTF using principal component analysis applied to complex values
(2014)
Principal components analysis (PCA) is frequently used for modelling the magnitude of the head related transfer functions (HRTFs). Assuming that the HRTFs are minimum phase systems, the phase is obtained from the Hilbert ...
Non-destructive genotypes classification and oil content prediction using near-infrared spectroscopy and chemometric tools in soybean breeding program
(2020-08-01)
In soybean (Glycine max L.) breeding programs, segregation is normally observed, and it is not possible to have replicates of individuals because each genotype is a unique copy. Therefore, near-infrared spectroscopy (NIRS) ...
TEACHING EXPERIMENT OF CHEMOMETRICS FOR EXPLORATORY ANALYSIS OF EDIBLE VEGETABLE OILS BY MID INFRARED SPECTROSCOPY AND PRINCIPAL COMPONENT ANALYSIS: A TUTORIAL. PART I.
(Soc Brasileira QuimicaSao PauloBrasil, 2012)
Principal Component Analysis Handbook
(Clanrye InternationalJersey City, 2015)
This book on Principal component analysis (PCA) is a significant contribution to the field of data analysis. PCA involves a statistical procedure which orthogonally transforms a set of possibly correlated observations into ...
Principal Component Analysis Handbook
(Clanrye InternationalJersey City, 2015)
This book on Principal component analysis (PCA) is a significant contribution to the field of data analysis. PCA involves a statistical procedure which orthogonally transforms a set of possibly correlated observations into ...