Subspace estimation and tracking using enhanced versions of Oja's algorithm
Samir Attallah, Karim Abed‐Meraim · 2002
We present two normalized versions of the Oja (1992) algorithm (NOja and NOOja) which can be used for the estimation of minor (noise) and principal (signal) subspaces of a vector sequence. The new algorithms offer, as compared to Oja, a faster convergence, a better orthogonality and numerical stability with a slight increase in computational complexity. These algorithms can find many applications, in particular, in wireless communications.