Optimal principal component analysis of STEM XEDS spectrum images.
Adv Struct Chem Imaging
; 5(1): 4, 2019.
Article
em En
| MEDLINE
| ID: mdl-31032174
ABSTRACT
STEM XEDS spectrum images can be drastically denoised by application of the principal component analysis (PCA). This paper looks inside the PCA workflow step by step on an example of a complex semiconductor structure consisting of a number of different phases. Typical problems distorting the principal components decomposition are highlighted and solutions for the successful PCA are described. Particular attention is paid to the optimal truncation of principal components in the course of reconstructing denoised data. A novel accurate and robust method, which overperforms the existing truncation methods is suggested for the first time and described in details.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Adv Struct Chem Imaging
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Alemanha