Principal Component Analysis (PCA). [PDF]
Tunis Med, 2021 Principal component analysis (PCA) was first defined in the form that is used nowadays by Pearson (1901). He found the best-fitting line in the least squares sense to the data points, which is known today as the first principal component. Hotelling (1933) showed that the loadings for the components are the eigenvectors of the sample covariance matrix ...
Ben Salem K, Ben Abdelaziz A.
europepmc +10 more sources
Parameter estimation of the structured illumination pattern based on principal component analysis (PCA): PCA-SIM [PDF]
Light: Science & Applications, 2023 Principal component analysis (PCA), a common dimensionality reduction method, is introduced into SIM to identify the frequency vectors and pattern phases of the illumination pattern with precise subpixel accuracy, fast speed, and noise-robustness, which ...
Xin Chen, Yiwei Hou, Peng Xi
doaj +2 more sources
The use of XLSTAT in conducting principal component analysis (PCA) when evaluating the relationships between sensory and quality attributes in grilled foods. [PDF]
MethodsX, 2020 Multivariate statistics is a tool for examining the relationship of multiple variables simultaneously. Principal component analysis (PCA) is an unsupervised multivariate analysis technique that simplifies the complexity of data by transforming them in a ...
Vidal NP +5 more
europepmc +2 more sources
Gender differences in dietary patterns and physical activity: an insight with principal component analysis (PCA). [PDF]
J Transl MedGender differences in dietary patterns and physical activity are known to influence metabolic health, but research exploring these differences using principal component analysis (PCA) is limited.
Feraco A +10 more
europepmc +2 more sources
Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm [PDF]
Energies, 2020 This research represents a conceptual shift in the process of introducing flexibility into power system frequency stability-related protection. The existing underfrequency load shedding (UFLS) solution, although robust and fast, has often proved to be ...
Tadej Skrjanc +2 more
doaj +3 more sources
Principal Component Analysis (PCA) [PDF]
Encyclopedia of Autism Spectrum Disorders, 2010 • Patternrecognition in high-dimensional spaces-P roblems arise when performing recognition in a high-dimensional space (e.g., curse of dimensionality).-S ignificant improvements can be achievedb yfi rst mapping the data into a lower-dimensionality space.
F. Husson, S. Lê, J. Pagès
semanticscholar +3 more sources
GrIP-PCA: Grassmann Iterative P-Norm Principal Component Analysis [PDF]
IEEE Open Journal of Signal Processing, 2020 Principal component analysis is one of the most commonly used methods for dimensionality reduction in signal processing. However, the most commonly used PCA formulation is based on the L2-norm, which can be highly influenced by outlier data.
Breton Minnehan +2 more
doaj +2 more sources
Evaluation of stretch reflex synergies in the upper limb using principal component analysis (PCA). [PDF]
PLoS ONE, 2023 The dynamic nature of movement and muscle activation emphasizes the importance of a sound experimental design. To ensure that an experiment determines what we intend, the design must be carefully evaluated.
Frida Torell
doaj +2 more sources
Introducing multiple factor analysis (MFA) as a diagnostic taxonomic tool complementing principal component analysis (PCA) [PDF]
ZooKeysMultiple factor analysis (MFA) is introduced as a diagnostic tool for taxonomy and discussed using examples from the herpetological literature. Its methodology and output are compared and contrasted to the more often used principal component analysis ...
L. Lee Grismer
doaj +4 more sources
PRINCIPAL COMPONENT ANALYSIS (PCA) DAN APLIKASINYA DENGAN SPSS
Jurnal Kesehatan Masyarakat Andalas, 2009 PCA (Principal Component Analysis ) are statistical techniques applied to a single set of variables when the researcher is interested in discovering which variables in the setform coherent subset that are relativity independent of one another.Variables ...
Hermita Bus Umar
doaj +2 more sources