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Analysing the Structure of Poly-crystalline Materials by 2-Dimensional DLS-Spectra and Neural Nets

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2206))

Abstract

A method to analyse the structure of poly-crystalline material by 2-dimensional DLS-Spectra and Backpropagation neural nets is introduced. It will be shown that DLS-Spectra “clean up” X-Ray-pictures such that the Radon-transformation of the Kikuchi-diagrams leads to better results. Further it will be shown, how these cleaned up Kikuchi-diagrams enable an automatic classification of poly-crystalline materials by neural hyper-classification systems based on the Backpropagation-algorithm.

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References

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© 2001 Springer-Verlag Berlin Heidelberg

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Reuter, M. (2001). Analysing the Structure of Poly-crystalline Materials by 2-Dimensional DLS-Spectra and Neural Nets. In: Reusch, B. (eds) Computational Intelligence. Theory and Applications. Fuzzy Days 2001. Lecture Notes in Computer Science, vol 2206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45493-4_43

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  • DOI: https://doi.org/10.1007/3-540-45493-4_43

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42732-2

  • Online ISBN: 978-3-540-45493-9

  • eBook Packages: Springer Book Archive

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