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Chemometric methods in analytical sp...
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Chu, Xiaoli.
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Chemometric methods in analytical spectroscopy technology
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Chemometric methods in analytical spectroscopy technology/ by Xiaoli Chu ... [et al.].
其他作者:
Chu, Xiaoli.
出版者:
Singapore :Springer Nature Singapore : : 2022.,
面頁冊數:
xiv, 595 p. :ill., digital ;24 cm.
內容註:
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.
Contained By:
Springer Nature eBook
標題:
Chemometrics. -
電子資源:
https://doi.org/10.1007/978-981-19-1625-0
ISBN:
9789811916250
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
Standard No.: 10.1007/978-981-19-1625-0doiSubjects--Topical Terms:
813967
Chemometrics.
LC Class. No.: QD75.4.C45
Dewey Class. No.: 543.015195
Chemometric methods in analytical spectroscopy technology
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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.
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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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