Interpretation of Mössbauer spectra in the energy and time domain with neural networks

H. Paulsen; R. Linder; F. Wagner; H. Winkler; S. J. Pöppl; A. X. Trautwein

doi:10.1023/A:1012606309138

Interpretation of Mössbauer spectra in the energy and time domain with neural networks

H. Paulsen^*, R. Linder, F. Wagner, H. Winkler, S. J. Pöppl, A. X. Trautwein

^*Corresponding author for this work

University of Kiel

5 Citations (Scopus)

Abstract

An artificial neural network for extracting reasonable and fast estimates of hyperfine parameters from Mössbauer spectra in the energy or time domain is outlined. First promising results for determining the asymmetry of the electric field gradient at the nucleus of a diamagnetic iron center as derived with different types of neural networks are reported.

Original language	English
Journal	Hyperfine Interactions
Volume	126
Issue number	1-4
Pages (from-to)	421-424
Number of pages	4
ISSN	0304-3843
DOIs	https://doi.org/10.1023/A:1012606309138
Publication status	Published - 01.12.2000

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10.1023/A:1012606309138

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abstract = "An artificial neural network for extracting reasonable and fast estimates of hyperfine parameters from M{\"o}ssbauer spectra in the energy or time domain is outlined. First promising results for determining the asymmetry of the electric field gradient at the nucleus of a diamagnetic iron center as derived with different types of neural networks are reported.",

author = "H. Paulsen and R. Linder and F. Wagner and H. Winkler and P{\"o}ppl, {S. J.} and Trautwein, {A. X.}",

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AU - Paulsen, H.

AU - Linder, R.

AU - Wagner, F.

AU - Winkler, H.

AU - Pöppl, S. J.

AU - Trautwein, A. X.

PY - 2000/12/1

Y1 - 2000/12/1

N2 - An artificial neural network for extracting reasonable and fast estimates of hyperfine parameters from Mössbauer spectra in the energy or time domain is outlined. First promising results for determining the asymmetry of the electric field gradient at the nucleus of a diamagnetic iron center as derived with different types of neural networks are reported.

AB - An artificial neural network for extracting reasonable and fast estimates of hyperfine parameters from Mössbauer spectra in the energy or time domain is outlined. First promising results for determining the asymmetry of the electric field gradient at the nucleus of a diamagnetic iron center as derived with different types of neural networks are reported.

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M3 - Journal articles

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EP - 424

JO - Hyperfine Interactions

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ER -

Interpretation of Mössbauer spectra in the energy and time domain with neural networks

Abstract

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