Convergence of alternative C-means clustering algorithms

Kiichi Urahama

Research output: Contribution to journalLetterpeer-review

3 Citations (Scopus)


The alternative c-means algorithm has recently been presented by Wu and Yang [1] for robust clustering of data. In this letter, we analyze the convergence of this algorithm by transforming it into an equivalent form with the Legendre transform. It is shown that this algorithm converges to a local optimal solution from any starting point.

Original languageEnglish
Pages (from-to)752-754
Number of pages3
JournalIEICE Transactions on Information and Systems
Issue number4
Publication statusPublished - Apr 2003
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture


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