Gravity inspired clustering algorithm

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Abstract

This paper presents a new clustering algorithm inspired by Newtonian gravity that iteratively groups data and eliminates outliers. In particular, we impose a grid over the region of interest and define a particle with data-dependent mass for each grid square. We then calculate a Newtonian inspired force on each of the particles and move them in the direction of the force. We repeat the process until there is no further movement. We compare performance with existing algorithms and show that in cases of medium to high clutter, our algorithm has an order of magnitude lower estimation error.

Original languageEnglish
Title of host publication2020, 14th International Conference on Signal Processing and Communication Systems, (ICSPCS)
Subtitle of host publicationproceedings
EditorsTadeusz A. Wysocki, Beata J. Wysocki
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9781728199726, 9781728199719
ISBN (Print)9781728199733
DOIs
Publication statusPublished - 2020
Event14th International Conference on Signal Processing and Communication Systems, ICSPCS 2020 - Virtual
Duration: 14 Dec 202016 Dec 2020

Conference

Conference14th International Conference on Signal Processing and Communication Systems, ICSPCS 2020
CityVirtual
Period14/12/2016/12/20

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