Orthogonal algorithm for minor and principal subspace extraction
A. Chkeif, Karim Abed‐Meraim, Yingbo Hua · 2003
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.