Orthogonal algorithm for minor and principal subspace extraction

Author

Chkeif, A. ; Abed-Meraim, K. ; Hua, Y.

Author_Institution

Dept. TSI, Telecom Paris, France

Volume

2

fYear

1999

fDate

1999

Firstpage

901

Abstract

This paper elaborates on an orthogonal version of the Oja (1992) method for the estimation of minor and principal subspace of a vector sequence. The proposed method, can extract principal components and if altered simply by the sign, it can also serve as a minor components extractor. This method has the same computational complexity as the Oja method, but it guarantees the orthogonality of the weight matrix at each iteration. Moreover, simulation results show that for minor subspace extraction the new algorithm is numerically more stable than the Oja algorithm

Keywords

computational complexity; feature extraction; matrix algebra; numerical stability; signal processing; Oja method; computational complexity; minor subspace estimation; minor subspace extraction; numerically stable algorithm; orthogonal algorithm; principal components analysis; principal components extraction; principal subspace estimation; principal subspace extraction; simulation results; vector sequence; weight matrix; Australia; Computational complexity; Covariance matrix; Data mining; Equations; Information analysis; Matrices; Principal component analysis; Signal processing algorithms; Telecommunications;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 1999. ISSPA '99. Proceedings of the Fifth International Symposium on

Conference_Location

Brisbane, Qld.

Print_ISBN

1-86435-451-8

Type

conf

DOI

10.1109/ISSPA.1999.815817

Filename

815817