Some Upper Bounds on Error Probability for Multiclass Pattern Recognition

Godfried T. Toussaint

Research output: Contribution to journalArticlepeer-review


Evaluation of the bound requires knowledge of a priori probabilities and of the class-condi-tional probability density functions. A tighter bound is obtained for the case of equal a priori probabilities, and a further bound is obtained that is independent of the a priori probabilities. An upper bound on the probability of error for the general pattern recognition problem is obtained as a functional of the pairwise Kolmogorov variational distances.

Original languageEnglish (US)
Pages (from-to)943-944
Number of pages2
JournalIEEE Transactions on Computers
Issue number8
StatePublished - Aug 1971

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics


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