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Spectral Reflectance Recovery from the Quadcolor Camera Signals Using the Interpolation and Weighted Principal Component Analysis Methods.

• Authors : Wen YC; Department of Electrophysics, National Yang Ming Chiao Tung University, No. 1001 University Road, Hsinchu 30010, Taiwan.; Wen S

Subjects: Diagnostic Imaging*; Principal Component Analysis

• Source: Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Aug 21; Vol. 22 (16). Date of Electronic Publication: 2022 Aug 21.Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220

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A Preliminary Study on the Differentiation of Linseed and Poppy Oil Using Principal Component Analysis Methods Applied to Fiber Optics Reflectance Spectroscopy and Diffuse Reflectance Imaging Spectroscopy.

• Authors : Amato SR; The Courtauld Institute of Art, Somerset House, Strand, London WC2R 0RN, UK.; Burnstock A

• Source: Sensors (Basel, Switzerland) [Sensors (Basel)] 2020 Dec 12; Vol. 20 (24). Date of Electronic Publication: 2020 Dec 12.Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220

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Application of linear solvation energy relationships and principal component analysis methods for the prediction of the retention behaviour of E-resveratrol analogues with substituted silica hydride stationary phases.

• Authors : Danylec B; Australian Centre for Research on Separation Science (ACROSS), School of Chemistry, Monash University, Melbourne, Victoria, 3800, Australia.; Kulsing C

• Source: Analytica chimica acta [Anal Chim Acta] 2019 Dec 20; Vol. 1090, pp. 159-171. Date of Electronic Publication: 2019 Sep 03.Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0370534 Publication Model: Print-Electronic Cited Medium: Internet ISSN:

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COMPARISON OF QUALITY CHARACTERISTICS IN HONEY USING GREY RELATIONAL ANALYSIS AND PRINCIPAL COMPONENT ANALYSIS METHODS.

• Source: Journal of Animal and Plant Sciences. February 28, 2018, Vol. 28 Issue 1, 252.

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Evaluating the performance of sparse principal component analysis methods in high-dimensional data scenarios.

• Authors : Bonner, Ashley J. (AUTHOR); Beyene, Joseph (AUTHOR)

Subjects: PRINCIPAL components analysis; DATA structures; GENE expression

• Source: Communications in Statistics: Simulation & Computation. 2017, Vol. 46 Issue 5, p3794-3811. 18p.

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Fast multidimensional completion and principal component analysis methods via the cosine product.

• Authors : Bentbib, A. H.; El Hachimi, A.; Jbilou, K.

Subjects: PRINCIPAL components analysis; DISCRETE cosine transforms; LINEAR orderings

• Source: Calcolo; Sep2022, Vol. 59 Issue 3, p1-33, 33p

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Single-trial evoked potentials study by combining wavelet denoising and principal component analysis methods.

• Authors : Zou L; School of Information Science and Engineering at the Jiangsu Polytechnic University, Jiangsu, China.; Zhang Y

Subjects: Evoked Potentials* ; Signal Processing, Computer-Assisted*; Brain/Brain/Brain/*physiology

• Source: Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society [J Clin Neurophysiol] 2010 Feb; Vol. 27 (1), pp. 17-24.Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 8506708 Publication Model: Print Cited Medium: Internet ISSN:

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Fault Detection and Isolation Using Interval Principal Component Analysis Methods

• Authors : IZEM, Tarek AIT; BOUGHELOUM, Wafa; HARKAT, Mohamed Faouzi

• Source: IFAC-PapersOnLine; January 2015, Vol. 48 Issue: 21 p1402-1407, 6p

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Comparison of two principal component analysis methods to evaluate reversed-phase retention data.

• Authors : Cserháti T; Central Research Institute for Chemistry, Hungarian Academy of Sciences, Budapest.; Illés Z

Subjects: Nitro Compounds/Nitro Compounds/Nitro Compounds/*analysis; Chromatography, Thin Layer/Chromatography, Thin Layer/Chromatography, Thin Layer/methods ; Regression Analysis

• Source: Journal of pharmaceutical and biomedical analysis [J Pharm Biomed Anal] 1991; Vol. 9 (9), pp. 685-91.Publisher: Elsevier Science Country of Publication: England NLM ID: 8309336 Publication Model: Print Cited Medium: Print ISSN: 0731-7085 (Print)

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COMPARISON OF QUALITY CHARACTERISTICS IN HONEY USING GREY RELATIONAL ANALYSIS AND PRINCIPAL COMPONENT ANALYSIS METHODS.

• Authors : Topal, M.; Yağanoğlu, A. M.

Subjects: MULTIPLE correspondence analysis (Statistics); PRINCIPAL components analysis; GREY relational analysis

• Source: JAPS: Journal of Animal & Plant Sciences; Apr2018, Vol. 28 Issue 2, p252-26, 12p, 6 Charts

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