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Orthogonal Oja algorithm

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4 Author(s)
Abed-Meraim, K. ; Telecom Paris, France ; Attallah, S. ; Chkeif, A. ; Hua, Y.

In this letter, we propose an orthogonalized version of the Oja 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.

Published in:

Signal Processing Letters, IEEE  (Volume:7 ,  Issue: 5 )