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Emitter recognition based on modified X-means clustering

  • Yasir Javed*
  • , A. I. Bhatti
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

This paper presents a new algorithm to divide multi-dimensional data into clusters. It enhances the K-Means clustering algorithm [1] so that the number of clusters is determined at run time. The paper uses radar classification problem as an example application. Most of naturally existing processes possess Gaussian distribution because of central limit theorem. This paper assumes that parameters of radars are Gaussian. Chi-Squared test for goodness of fit is used for evaluating the hypothesized distribution from sampled data. The data is divided and output of chi-squared test is used to decide whether to carry on sub-clustering or not. Test results on simulated data are shown to demonstrate the working of algorithm.

Original languageEnglish
Title of host publicationProceedings - Thirteenth International Symposium on Temporal Representation and Reasoning, TIME 2006
Pages352-358
Number of pages7
DOIs
StatePublished - 2005
Externally publishedYes
EventIEEE 2005 International Conference on Emerging Technologies, ICET 2005 - Islamabad, Pakistan
Duration: 17 Sep 200518 Sep 2005

Publication series

NameProceedings - IEEE 2005 International Conference on Emerging Technologies, ICET 2005
Volume2005

Conference

ConferenceIEEE 2005 International Conference on Emerging Technologies, ICET 2005
Country/TerritoryPakistan
CityIslamabad
Period17/09/0518/09/05

ASJC Scopus subject areas

  • General Engineering

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