A modified PCA based on the minimum error entropy

Z.H. Guo, H. Yue, H. Wang

Research output: Contribution to conferencePaper

7 Citations (Scopus)

Abstract

Conventional principal component analysis (PCA) minimizes the total error variance, which may be inappropriate for the non-Gaussian distribution systems. In this paper the entropy is proposed as a more general index for PCA model, and then a modified PCA with the optimization for the minimum error entropy via a genetic algorithm (GA) is addressed.
Original languageEnglish
Pages3800-3801
Number of pages2
Publication statusPublished - Jun 2004
EventAmerican Control Conference 2004 - Boston, United States
Duration: 30 Jun 20042 Jul 2004

Conference

ConferenceAmerican Control Conference 2004
CountryUnited States
CityBoston
Period30/06/042/07/04

Keywords

  • modified pca
  • minimum
  • error entropy
  • genetic algorithms
  • principal component analysis
  • minimum entropy methods
  • least mean squares methods

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