Results 281 to 290 of about 2,300,147 (337)

Principal Component Analysis Based Quaternion-Valued Medians for Non-Invasive Blood Glucose Estimation. [PDF]

Sensors (Basel)
Feng J, Ling BW.
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Cognitive modes involved in emotion regulation identified using Constrained Principal Component Analysis for fMRI (fMRI-CPCA)

van Reekum CM, Tupitsa E, Lloyd WK, Momeni A, Shahki J, Feredoes E, Woodward TS.   +6 more
europepmc   +1 more source

A novel hybrid model for species distribution prediction using probabilistic random forest, principal component analysis and genetic algorithm. [PDF]

PLoS One
Adekunle TA, Ogundoyin IK, Akanbi CO.
europepmc   +1 more source

Position-specific workload and performance analysis in professional rugby union: Insights from global positioning system data and principal component analysis. [PDF]

PLoS One
Ren X, Boisbluche S, Philippe K, Demy M, Hu Z, Ding S, Prioux J.   +6 more
europepmc   +1 more source

Unraveling the Molecular Inhibition and Conformational Changes of Hsp70 and Hsc70 Induced by VER-155008, a Competitive ATPase Inhibitor through Molecular Dynamics Simulations and Principal Component Analysis. [PDF]

ACS Omega
Barbosa da Silva MC, Falabelo CGS, Leonardo ES, Oliveira C, Valente RPDP, Lima AH, Farias SAS, Nagata K, da Costa KS, Taube PS.   +9 more
europepmc   +1 more source

Feature reduction using minimum noise fraction and principal component analysis transforms for improving the classification of hyperspectral image

, 2017
et.al Murinto Nur
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Temporal dynamic of cognitive decline in type 2 diabetes mellitus patients: a multimodal biomarker analysis using event-based modal and principal component analysis. [PDF]

Diabetol Metab Syndr
Ni MH, Hu B, Bai XY, Tong Y, Ma ZY, Xie H, Cao XY, Cui YY, Li SN, Dai P, Du LJ, Yu XW, Yan LF, Gao B, Yu Y, Cui GB.   +15 more
europepmc   +1 more source

Principal Component Analysis in Space Forms. [PDF]

IEEE Trans Signal Process
Tabaghi P, Khanzadeh M, Wang Y, Mirarab S.   +3 more
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Coupled Principal Component Analysis

IEEE Transactions on Neural Networks, 2004
A framework for a class of coupled principal component learning rules is presented. In coupled rules, eigenvectors and eigenvalues of a covariance matrix are simultaneously estimated in coupled equations. Coupled rules can mitigate the stability-speed problem affecting noncoupled learning rules, since the convergence speed in all eigendirections of the
Möller, Ralf, Könies, Axel
openaire   +5 more sources