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Artificial neural network techniques for analysis of ion backscattering spectra

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conference contribution
posted on 06.12.2017, 00:00 by Minmei LiMinmei Li, Xiaolong FanXiaolong Fan, Brijesh VermaBrijesh Verma, Ronald BalsysRonald Balsys, D O'Connor
Ion backscattering spectrometry is an analysis technology that is dedicated to the compositional analysis of samples with the thickness of μm level. The problem of spectral data analysis, which is to determine the sample structure from the measured spectra, is generally ill-posed. In this study, artificial neural network (ANN) techniques have been developed for spectral data analysis. A multilayer feedforward neural network was constructed and applied to the specific case of SiGe thin films on a silicon substrate. The network was trained by the resilient backpropagation algorithm with hundreds of simulated spectra of samples for which the structures are known. Then the trained network was applied to analyse spectra with unknown structure of samples. The ANN prediction results are excellent. The constructed neural network can handle properly redundancies, which were caused by the constraint of output variables.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Start Page

1

End Page

7

Number of Pages

7

Start Date

01/01/2005

ISBN-10

1932415661

Location

Las Vegas, USA

Publisher

CSREA Press

Place of Publication

Las Vegas

Peer Reviewed

Yes

Open Access

No

Era Eligible

Yes

Name of Conference

International Conference on Artificial Intelligence