Principal curves with bounded turn

Sathyakama Sandilya, Sanjeev R. Kulkarni

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


Principal curves, like principal components, are a tool used in multivariate analysis for ends like feature extraction. Defined in their original form, principal curves need not exist for general distributions. The existence of principal curves with bounded length for any distribution that satisfies some minimal regularity conditions has been shown. We define principal curves with bounded turn, show that they exist, and present a learning algorithm for them. Principal components are a special case of such curves when the turn is zero.

Original languageEnglish (US)
Pages (from-to)2789-2793
Number of pages5
JournalIEEE Transactions on Information Theory
Issue number10
StatePublished - Oct 2002

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


  • Bounded turn
  • Curve fitting
  • Feature extraction
  • Learning
  • Multivariate analysis
  • Principal components
  • Principal curves


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