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Chemometric methods in analytical spectroscopy technology

Record Type:	Electronic resources : Monograph/item
Title/Author:	Chemometric methods in analytical spectroscopy technologyby Xiaoli Chu ... [et al.].
other author:	Chu, Xiaoli.
Published:	Singapore :Springer Nature Singapore :2022.
Description:	xiv, 595 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Chemometrics.
Online resource:	https://doi.org/10.1007/978-981-19-1625-0
ISBN:	9789811916250$q(electronic bk.)

Chemometric methods in analytical spectroscopy technology
Chemometric methods in analytical spectroscopy technology[electronic resource] /by Xiaoli Chu ... [et al.]. - Singapore :Springer Nature Singapore :2022. - xiv, 595 p. :ill., digital ;24 cm.

Introduction -- Modern Spectroscopic Analysis Technology -- Basis of Matrix and Mathematical Statistics -- Preprocessing Methods in Spectroscopy Analysis -- Wavelength Variable Selection Method -- Spectral Dimensionality Reduction Method -- Linear Regression Method -- Non-Linear Regression Method -- Selection of Representative samples -- Outlier Detection Method -- Calibration Model Maintenance -- Pattern Recognition -- Evaluation of Model Performance -- Ways to Improve Model Predictive Ability -- Multi-spectral Fusion Technology -- Multi-way Resolution and Calibration -- Calibration Transfer Method -- Deep Learning Algorithms -- Chemometrics Software and Toolbox -- Discussions.

This book discusses chemometric methods for spectroscopy analysis including NIR, MIR, Raman, NMR, and LIBS, from the perspective of practical applied spectroscopy. It covers all aspects of chemometrics associated with analytical spectroscopy, including representative sample selection algorithm, outlier detection algorithm, model updating and maintenance algorithm and strategy and calibration performance evaluation methods.To provide a systematic and comprehensive overview the latest progress of chemometric methods including recent scientific research and practical applications are presented. In addition the book also highlights the improvement of classical algorithms and the extension of common strategies. It is therefore useful as a reference book for researchers engaged in analytical spectroscopy technology, chemometrics, analytical instruments and other related fields.

ISBN: 9789811916250$q(electronic bk.)

Standard No.: 10.1007/978-981-19-1625-0doiSubjects--Topical Terms:

265647
Chemometrics.

LC Class. No.: QD75.4.C45

Dewey Class. No.: 543.015195

Chemometric methods in analytical spectroscopy technology
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245 0 0 $a Chemometric methods in analytical spectroscopy technology $h [electronic resource] / $c by Xiaoli Chu ... [et al.].
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300 $a xiv, 595 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- Modern Spectroscopic Analysis Technology -- Basis of Matrix and Mathematical Statistics -- Preprocessing Methods in Spectroscopy Analysis -- Wavelength Variable Selection Method -- Spectral Dimensionality Reduction Method -- Linear Regression Method -- Non-Linear Regression Method -- Selection of Representative samples -- Outlier Detection Method -- Calibration Model Maintenance -- Pattern Recognition -- Evaluation of Model Performance -- Ways to Improve Model Predictive Ability -- Multi-spectral Fusion Technology -- Multi-way Resolution and Calibration -- Calibration Transfer Method -- Deep Learning Algorithms -- Chemometrics Software and Toolbox -- Discussions.
520 $a This book discusses chemometric methods for spectroscopy analysis including NIR, MIR, Raman, NMR, and LIBS, from the perspective of practical applied spectroscopy. It covers all aspects of chemometrics associated with analytical spectroscopy, including representative sample selection algorithm, outlier detection algorithm, model updating and maintenance algorithm and strategy and calibration performance evaluation methods.To provide a systematic and comprehensive overview the latest progress of chemometric methods including recent scientific research and practical applications are presented. In addition the book also highlights the improvement of classical algorithms and the extension of common strategies. It is therefore useful as a reference book for researchers engaged in analytical spectroscopy technology, chemometrics, analytical instruments and other related fields.
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650 0 $a Spectrum analysis. $3 188665
650 1 4 $a Spectroscopy. $3 737192
650 2 4 $a Analytical Chemistry. $3 273936
650 2 4 $a Linear Models and Regression. $3 913351
700 1 $a Chu, Xiaoli. $3 921425
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856 4 0 $u https://doi.org/10.1007/978-981-19-1625-0
950 $a Chemistry and Materials Science (SpringerNature-11644)