Application of neural networks using quadratic junctions in cluster analysis

Mu Chun Su, Ta Kang Liu

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


In this paper, we explore an unsupervised learning algorithm for a class of neural networks with quadratic neural-type junctions. The objective of the networks incorporated with the proposed unsupervised learning algorithm is to cluster data. The detected clusters may be either hyperspherical-shaped or hyperellipsoidal-shaped. Two data sets are tested to illustrate the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)165-175
Number of pages11
Issue number1-4
StatePublished - 2001


  • Cluster analysis
  • Competitive learning
  • Neural networks
  • Unsupervised learning


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