A square root merit function for canonical correlation analysis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Canonical Correlation Analysis (CCA) is a well-known technique in multivariate statistical analysis, which has been widely used in economics, meteorology, and in many modern information processing fields. This paper proposes many dynamical systems for computing canonical correlations and canonical variates. These systems are shown to converge to the actual components rather than to a subspace spanned by these components. Qualitative properties of the proposed systems are analyzed in detail including the limit of solutions as time approaches infinity. Convergence is illustrated by a numerical example.

Original languageEnglish (US)
Title of host publication2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009
Pages2473-2476
Number of pages4
DOIs
StatePublished - Oct 26 2009
Event2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009 - Taipei, Taiwan, Province of China
Duration: May 24 2009May 27 2009

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Other

Other2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009
CountryTaiwan, Province of China
CityTaipei
Period5/24/095/27/09

Keywords

  • Canonical correlation analysis
  • Polynomial dynamical systems
  • Square root merit function

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