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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© 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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Print ISBN: 978-3-540-42732-2
Online ISBN: 978-3-540-45493-9
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