On the choice of tuning parameters for use with Robust GCV, Modified GCV and the Discrepancy Principle in the inversion of ARXPS data

Autor:	R.W. Paynter, Daniel Peykov
Rok vydání:	2014
Předmět:	Radiation Inversion (meteorology) Ranging Condensed Matter Physics Atomic and Molecular Physics and Optics Matrix model Electronic Optical and Magnetic Materials Tikhonov regularization Data Noise Applied mathematics Physical and Theoretical Chemistry Optimal tuning Spectroscopy Mathematics
Zdroj:	Journal of Electron Spectroscopy and Related Phenomena. 197:93-101
ISSN:	0368-2048
DOI:	10.1016/j.elspec.2014.09.011
Popis:	Composition depth profiles were extracted from simulated ARXPS data using regularization, with the regularization parameter determined by three different methods (Robust GCV, Modified GCV, and the Discrepancy Principle) that require tuning parameters. For each method, the optimal tuning parameter was determined for two input profile shapes, three Tikhonov regulators (0th, 1st, and 2nd order), and data noise ranging from 1% to 9%. Although universally applicable optimal tuning parameters were not identified, it was found that certain values could consistently produce acceptable results for the input profiles used in this study.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::68dc6c5772841b7eaf6d953844879a36 https://doi.org/10.1016/j.elspec.2014.09.011 Zobrazit plný text záznamu Full Text from ScienceDirect