Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-28T23:25:23.238Z Has data issue: false hasContentIssue false
  • English
  • Français

A Novel Method for Automatic Determination of the Number of Meaningful Components in the PCA Analysis of Spectrum-Images

Published online by Cambridge University Press:  01 August 2018

Pavel Potapov ,
Paolo Longo  and
Axel Lubk
Pavel Potapov
Affiliation:
Leibniz Institute for Solid State and Materials Research (IFW), Dresden, Germany Technical University of Dresden, Department of Physics, Dresden, Germany
Paolo Longo
Affiliation:
Gatan Inc, Pleasanton, CA, USA
Axel Lubk
Affiliation:
Technical University of Dresden, Department of Physics, Dresden, Germany

Abstract

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Abstract
Information
Microscopy and Microanalysis , Volume 24 , Supplement S1: Proceedings of Microscopy & Microanalysis 2018 , August 2018 , pp. 572 - 573
Copyright
© Microscopy Society of America 2018 

References

[1] exemplary Watanabe, M., Okunishi, E. Ishizuka, K. Microsc. Anal. 23(7 2009) p. 5.Google Scholar
[2] exemplary Gavish, M. Donoho, D. L. IEEE Trans. Information Theory 60 2014) p. 5040.Google Scholar
[3] PP and AL designed the treatment algorithms and PL acquired the experimental spectrum-images.Google Scholar
[4] PP acknowledges funding from DFG “Zukunftskonzept” (F-003661-553-U6a-1020605).Google Scholar
[5] AL received funding ERC under the Horizon 2020 program (grant 715620).Google Scholar