Modulo similarity in comparing histograms
- https://doi.org/10.2991/ifsa-eusflat-15.2015.57How to use a DOI?
- Histograms, comparison, ukasiewicz logic, similarity, modulo similarity.
Histograms are a tool for graphical representation of frequency data and thus helpful in creating a fast understanding of, e.g., contents of frequency data. Comparing histograms is topic of increasing importance due to an increase in the availability of data sets containing frequency information. Automatic data collection from “everywhere” has made collection of frequency data very common. As many different types of similarities exist, our focus is on ukasiewicz logic-based similarity and we present two new measures, the “modulo similarity” measure and the “maximum pair assignment compatibility” measure. These measures do not use PDF conversion, or vector-based approaches, in the comparison of histograms, but concentrate on the data samples used to form histograms. We illustrate the usefulness of these measures with numerical examples.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Pasi Luukka AU - Mikael Collan PY - 2015/06 DA - 2015/06 TI - Modulo similarity in comparing histograms BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 393 EP - 397 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.57 DO - https://doi.org/10.2991/ifsa-eusflat-15.2015.57 ID - Luukka2015/06 ER -