DIMENSIONALITY REDUCTION OF MULTI-VARIATE LASER SPECTROSCOPY DATA

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F18%3APU130588" target="_blank" >RIV/00216305:26620/18:PU130588 - isvavai.cz</a>
Result on the web
<a href="http://16cssc2018.spektroskopie.cz/files/CSSC_2018_BOOK_OF_ABSTRACTS_FINAL.pdf" target="_blank" >http://16cssc2018.spektroskopie.cz/files/CSSC_2018_BOOK_OF_ABSTRACTS_FINAL.pdf</a>
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
DIMENSIONALITY REDUCTION OF MULTI-VARIATE LASER SPECTROSCOPY DATA
Original language description
State-of-the-art Laser-Induced Breakdown Spectroscopy (LIBS) instruments enable high repetition rate analysis. With this experimental settings, the mapping of sample surfaces provides large data sets. The richness of information is in spectra (objects) as well as wavelengths (variables). Processing such multivariate data is, thus, a challenging task demanding more sophisticated approaches. Utilization of advanced statistical algorithms, referred to as multivariate data analysis algorithms or chemometrics, are of great interest in contemporary data processing [1-3]. Moreover, elemental composition (relation of individual elements) and structural complexity (relation of individual matrices) provides additional valuable information in understanding of the heterogeneity of, e.g., biological and geological samples. In our work, we bring an introduction to the utilization of Principal Component Analysis to processing of LIBS data. Our efforts tackled mainly the dimensionality reduction in both, objects and
Czech name
—
Czech description
—

Project
<a href="/en/project/LQ1601" target="_blank" >LQ1601: CEITEC 2020</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)