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Article
Information Theory Approach to Crystallographic Symmetry Classifications of Noisy 2D Periodic Images
2018 IEEE 13th Nanotechnology Materials and Devices Conference (NMDC)
  • Peter Moeck, Portland State University
Document Type
Citation
Publication Date
1-1-2019
Disciplines
Abstract

An information theory inspired approach, i.e. utilization of Geometric Akaike Information Criteria (G-AICs), individual Akaike weights, and products of Akaike weights, allows for objective crystallographic symmetry classification of images that are more or less periodic in two dimensions (2D). The combined usage of G-AICs for Bravais lattice types and plane symmetry groups should enable successful classifications even in the presence of severe pseudo-symmetry challenges.

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© Copyright 2019 IEEE - All rights reserved.

DOI
10.1109/NMDC.2018.8605865
Persistent Identifier
https://archives.pdx.edu/ds/psu/29052
Citation Information
P. Moeck, "Information Theory Approach to Crystallographic Symmetry Classifications of Noisy 2D Periodic Images," 2018 IEEE 13th Nanotechnology Materials and Devices Conference (NMDC), Portland, OR, 2018, pp. 1-4.