Unconstrained functional criteria for canonical correlation analysis

Research output: Contribution to journalConference articlepeer-review

Abstract

Unconstrained and constrained optimization criteria for extracting multiple true canonical variates and canonical correlations are proposed. These include a weighted information criterion (WINC-CCA) and a shifted information criterion (SINC-CCA) for searching the optimal solutions. The gradient flows of the proposed CCA functions are analyzed and some of their convergence properties are presented. The main feature of this approach is that the actual canonical variates are automatically obtained. Based on the gradient-ascent method, many algorithms for performing the true CCA recursively are provided.

Original languageEnglish (US)
Article number1465088
Pages (from-to)2317-2320
Number of pages4
JournalProceedings - IEEE International Symposium on Circuits and Systems
DOIs
StatePublished - Dec 1 2005
EventIEEE International Symposium on Circuits and Systems 2005, ISCAS 2005 - Kobe, Japan
Duration: May 23 2005May 26 2005

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