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Stable and Orthonormal OJA Algorithm With Low Complexity

delete2011-04-01
delete5
PRE
AI
R
Rong Wang *
M
Minli Yao
D
Daoming Zhang
H
Hongxing Zou
DOI:10.1109/LSP.2011.2108999delete
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Abstract

Abstract

En 中文
In this letter, a stable and orthonormal version of the OJA algorithm (SOOJA) is investigated for principal and minor subspace extraction and tracking. The new algorithm presented here guarantees the orthonormality of the weight matrix at each iteration through a novel orthonormalization method. Moreover, it obtains both a high numerical stability and a low computational complexity. The superiority of the proposed algorithm to some existing subspace tracking algorithms is demonstrated using a classical example. Simulation results confirm the veracity of the subspace tracking algorithm advocated.
Keywords:
Numerical stability
OJA algorithm
subspace tracking
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IEEE Signal Processing Magazine cover
IEEE Signal Processing Magazine
IF:
9.6
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1.7W

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T
tsinghua university
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Rocket Force University of Engineering
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