Self-stabilized minor subspace extraction algorithm based on Householder transformation
Karim Abed‐Meraim, Samir Attallah, A. Chkeif, Yingbo Hua · 2002
In this paper, we propose an orthogonalized version of Oja's algorithm (OOja) that can be used for the estimation of minor and principal subspaces of a vector sequence. The new algorithm offers, as compared to Oja, such advantages as orthogonality of the weight matrix, which is ensured at each iteration, numerical stability and a quite similar computational complexity.