Untitled - IAP/TU Wien - Technische Universität Wien

71st IUVSTA Workshop
Utilizing Artificial Neural Networks for the Automation of Auger Spectra
Analysis
Besnik Poniku, 1,* Igor Beli!, 1 and Monika Jenko 1
1 Institute of Metals and Technology, Lepi pot 11, Ljubljana, Slovenia
*besnik.poniku@imt.si
The use of Artificial Neural Networks (ANN) is a quick and efficient way for analyzing data for
different purposes. Apart from realizing relationships within a set of measured data, ANN may be also
trained with a set of data containing specific features, and then look for a match of the learned feature in a
new set of data.
These properties of ANN are very useful in our research work when we have in mind that the main
goal of our work is the full automation of the Auger spectra analysis. The relationship realization capability
of the ANN was used to “deconstruct” the standard Auger spectrum of various elements into its parts as a
necessary step to build the Auger spectra simulator which would later be used to test algorithms for
background removal and noise reduction. The fact that we were not looking for the justification on the
physical basis but were taking into consideration features as they were needs to be emphasized here, and
ANN are capable of predicting relationships in a given data without knowing the details of the physical
phenomena behind it, i.e. without presenting an equation to the program. Having the pattern matching
capability on the other hand yet unexplored in this context we think that ANN can be utilized in a variety of
ways to analyze the Auger spectra, and through this contribution we aim to shed more light into the strengths
and weaknesses of using such an approach for the aforementioned purpose.
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