Title

Information Theory Approach to Crystallographic Symmetry Classifications of Noisy 2D Periodic Images

Published In

2018 IEEE 13th Nanotechnology Materials and Devices Conference (NMDC)

Document Type

Citation

Publication Date

1-2019

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.

Description

© Copyright 2019 IEEE - All rights reserved.

DOI

10.1109/NMDC.2018.8605865

Persistent Identifier

https://archives.pdx.edu/ds/psu/29052

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