Title :
A square root merit function for Canonical Correlation Analysis
Author :
Hasan, Mohammed A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Minnesota Duluth, Duluth, MN, USA
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.
Keywords :
correlation methods; covariance matrices; eigenvalues and eigenfunctions; statistical analysis; canonical correlation analysis; canonical variates; covariance matrix; economics; eigenvalue problems; information processing field; meteorology; multivariate statistical analysis; square root merit function; Convergence of numerical methods; H infinity control; Information analysis; Information processing; Linear discriminant analysis; Meteorology; Polynomials; Principal component analysis; Statistical analysis; Vectors; canonical correlation analysis; polynomial dynamical systems; square root merit function;
Conference_Titel :
Circuits and Systems, 2009. ISCAS 2009. IEEE International Symposium on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-3827-3
Electronic_ISBN :
978-1-4244-3828-0
DOI :
10.1109/ISCAS.2009.5118302
