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Cross-talk correction method for knee kinematics in gait analysis using principal component analysis (PCA): a new proposal
Cross-talk correction method for knee kinematics in gait analysis using principal component analysis (PCA): a new proposal
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Cross-talk correction method for knee kinematics in gait analysis using principal component analysis (PCA): a new proposal

Baudet, Audrey ; Morisset, Claire ; d'Athis, Philippe ; Maillefert, Jean-Francis ; Casillas, Jean-Marie ; Ornetti, Paul ; Laroche, Davy Fasano, Alfonso

PloS one, 2014-07, Vol.9 (7), p.e102098-e102098 [Periódico revisado por pares]

United States: Public Library of Science

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2
Variance The Estimation Eigen Value of Principal Component Analysis and Nonlinear Principal Component Analysis
Variance The Estimation Eigen Value of Principal Component Analysis and Nonlinear Principal Component Analysis
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Variance The Estimation Eigen Value of Principal Component Analysis and Nonlinear Principal Component Analysis

Makkulau ; Tenri Ampa, Andi ; Yahya, Irma ; La Ome, Lilis ; Saidi, La Ode Sanusi, W. ; Naufal, M.A. ; Chen, W.-H. ; Side, S. ; Abd Hamid, N.Z.

ITM web of conferences, 2024, Vol.58, p.4001 [Periódico revisado por pares]

EDP Sciences

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3
Untangling the complexity of market competition in consumer goods-A complex Hilbert PCA analysis
Untangling the complexity of market competition in consumer goods-A complex Hilbert PCA analysis
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Untangling the complexity of market competition in consumer goods-A complex Hilbert PCA analysis

Mizuno, Makoto ; Aoyama, Hideaki ; Fujiwara, Yoshi Gross, Thilo

PloS one, 2021-02, Vol.16 (2), p.e0245531-e0245531 [Periódico revisado por pares]

United States: Public Library of Science

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4
Traffic Crash Severity Prediction-A Synergy by Hybrid Principal Component Analysis and Machine Learning Models
Traffic Crash Severity Prediction-A Synergy by Hybrid Principal Component Analysis and Machine Learning Models
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Traffic Crash Severity Prediction-A Synergy by Hybrid Principal Component Analysis and Machine Learning Models

Assi, Khaled

International journal of environmental research and public health, 2020-10, Vol.17 (20), p.7598 [Periódico revisado por pares]

Switzerland: MDPI AG

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5
Use of Machine Learning and Principal Component Analysis to Retrieve Nitrogen Dioxide (NO2) With Hyperspectral Imagers and Reduce Noise in Spectral Fitting
Use of Machine Learning and Principal Component Analysis to Retrieve Nitrogen Dioxide (NO2) With Hyperspectral Imagers and Reduce Noise in Spectral Fitting
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Use of Machine Learning and Principal Component Analysis to Retrieve Nitrogen Dioxide (NO2) With Hyperspectral Imagers and Reduce Noise in Spectral Fitting

Joiner, Joanna ; Marchenko, Sergey ; Fasnacht, Zachary ; Lamsal, Lok ; Li, Can ; Vasilkov, Alexander ; Krotkov, Nickolay

Atmospheric measurement techniques, 2023-01, Vol.16 (2), p.481-500 [Periódico revisado por pares]

Goddard Space Flight Center: European Geosciences Union

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6
Comparison of Independent Component Analysis, Principal Component Analysis, and Minimum Noise Fraction Transformation for Tree Species Classification Using APEX Hyperspectral Imagery
Comparison of Independent Component Analysis, Principal Component Analysis, and Minimum Noise Fraction Transformation for Tree Species Classification Using APEX Hyperspectral Imagery
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Comparison of Independent Component Analysis, Principal Component Analysis, and Minimum Noise Fraction Transformation for Tree Species Classification Using APEX Hyperspectral Imagery

Dabiri, Zahra ; Lang, Stefan

ISPRS international journal of geo-information, 2018-12, Vol.7 (12), p.488 [Periódico revisado por pares]

Basel: MDPI AG

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7
Application of Unsupervised Learning for the Evaluation of Aerogels' Efficiency towards Dye Removal-A Principal Component Analysis (PCA) Approach
Application of Unsupervised Learning for the Evaluation of Aerogels' Efficiency towards Dye Removal-A Principal Component Analysis (PCA) Approach
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Application of Unsupervised Learning for the Evaluation of Aerogels' Efficiency towards Dye Removal-A Principal Component Analysis (PCA) Approach

Younes, Khaled ; Kharboutly, Yahya ; Antar, Mayssara ; Chaouk, Hamdi ; Obeid, Emil ; Mouhtady, Omar ; Abu-Samha, Mahmoud ; Halwani, Jalal ; Murshid, Nimer

Gels, 2023-04, Vol.9 (4), p.327 [Periódico revisado por pares]

Switzerland: MDPI AG

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8
Application of Unsupervised Machine Learning for the Evaluation of Aerogels' Efficiency towards Ion Removal-A Principal Component Analysis (PCA) Approach
Application of Unsupervised Machine Learning for the Evaluation of Aerogels' Efficiency towards Ion Removal-A Principal Component Analysis (PCA) Approach
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Application of Unsupervised Machine Learning for the Evaluation of Aerogels' Efficiency towards Ion Removal-A Principal Component Analysis (PCA) Approach

Younes, Khaled ; Kharboutly, Yahya ; Antar, Mayssara ; Chaouk, Hamdi ; Obeid, Emil ; Mouhtady, Omar ; Abu-Samha, Mahmoud ; Halwani, Jalal ; Murshid, Nimer

Gels, 2023-04, Vol.9 (4), p.304 [Periódico revisado por pares]

Switzerland: MDPI AG

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9
Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data
Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data
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Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data

Salvatore, Stefania ; Bramness, Jørgen G ; Røislien, Jo

BMC medical research methodology, 2016-07, Vol.16 (1), p.81-81, Article 81 [Periódico revisado por pares]

England: BioMed Central Ltd

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10
Training Design, Performance Analysis, and Talent Identification-A Systematic Review about the Most Relevant Variables through the Principal Component Analysis in Soccer, Basketball, and Rugby
Training Design, Performance Analysis, and Talent Identification-A Systematic Review about the Most Relevant Variables through the Principal Component Analysis in Soccer, Basketball, and Rugby
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Training Design, Performance Analysis, and Talent Identification-A Systematic Review about the Most Relevant Variables through the Principal Component Analysis in Soccer, Basketball, and Rugby

Pino-Ortega, José ; Rojas-Valverde, Daniel ; Gómez-Carmona, Carlos D ; Rico-González, Markel

International journal of environmental research and public health, 2021-03, Vol.18 (5), p.2642 [Periódico revisado por pares]

Switzerland: MDPI AG

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