On the utilization of principal component analysis in laser-induced breakdown spectroscopy data analysis, a review

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F18%3APU128293" target="_blank" >RIV/00216305:26620/18:PU128293 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.sab.2018.05.030" target="_blank" >http://dx.doi.org/10.1016/j.sab.2018.05.030</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.sab.2018.05.030" target="_blank" >10.1016/j.sab.2018.05.030</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On the utilization of principal component analysis in laser-induced breakdown spectroscopy data analysis, a review

Popis výsledku v původním jazyce

An implementation of a fast, robust, and effective algorithm is inevitable in modern multivariate data analysis (MVDA). The principal component analysis (PCA) algorithm is becoming popular not only in the spectroscopic community because it complies with the qualities mentioned above. PCA is, therefore, often used for the rocessing of detected multivariate signal (characteristic spectra). Over the past decade, PCA has been adopted by the Laser-Induced Breakdown Spectroscopy (LIBS) community and the number of scientific articles referring to PCA steadily increases. The interest in PCA is not caused only by the basic need to obtain a fast data visualization on a lower dimensional scale and to inspect the most prominent variables. Most recently, PCA has also been applied to yield unconventional data analyses, i.e. processing of large scale LIBS maps. However, a rapid development of LIBS-related instrumentation and applications has led to some non-uniform methodologies in the implementation and utilization of MVDA, including PCA. Thus, in this work, we critically assess and elaborate on the approaches to utilize PCA in LIBS data processing. The aim of this article is also to derive some implications and to suggest advice in data preprocessing, visualization, dimensionality reduction, model building, classification, quantification and non-conventional multivariate mapping. This review reflects also other MVDA algorithms than PCA and consequently, presented conclusions and recommendations can be generalized.

Název v anglickém jazyce

On the utilization of principal component analysis in laser-induced breakdown spectroscopy data analysis, a review

Popis výsledku anglicky

An implementation of a fast, robust, and effective algorithm is inevitable in modern multivariate data analysis (MVDA). The principal component analysis (PCA) algorithm is becoming popular not only in the spectroscopic community because it complies with the qualities mentioned above. PCA is, therefore, often used for the rocessing of detected multivariate signal (characteristic spectra). Over the past decade, PCA has been adopted by the Laser-Induced Breakdown Spectroscopy (LIBS) community and the number of scientific articles referring to PCA steadily increases. The interest in PCA is not caused only by the basic need to obtain a fast data visualization on a lower dimensional scale and to inspect the most prominent variables. Most recently, PCA has also been applied to yield unconventional data analyses, i.e. processing of large scale LIBS maps. However, a rapid development of LIBS-related instrumentation and applications has led to some non-uniform methodologies in the implementation and utilization of MVDA, including PCA. Thus, in this work, we critically assess and elaborate on the approaches to utilize PCA in LIBS data processing. The aim of this article is also to derive some implications and to suggest advice in data preprocessing, visualization, dimensionality reduction, model building, classification, quantification and non-conventional multivariate mapping. This review reflects also other MVDA algorithms than PCA and consequently, presented conclusions and recommendations can be generalized.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10301 - Atomic, molecular and chemical physics (physics of atoms and molecules including collision, interaction with radiation, magnetic resonances, Mössbauer effect)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Spectrochimica Acta Part B

ISSN

0584-8547

e-ISSN

—

Svazek periodika

148

Číslo periodika v rámci svazku

-

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

19

Strana od-do

65-82

Kód UT WoS článku

000445311800009

EID výsledku v databázi Scopus

2-s2.0-85048439338