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Fast algorithms for subspace tracking
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DOI：10.1109/97.928678.png)
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Abstract
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In this letter, we present two normalized versions of Oja's algorithm (NOja and NOOja), which can be used for the estimation of minor and principal subspaces of a vector sequence. The new algorithms offer, as compared to Oja, a faster convergence, orthogonality, and a better numerical stability with a slight increase in computational complexity.
Keywords:
numerical stability
normalized Oja
Oja's algorithm
orthogonal Oja
subspace estimation
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