Bi-iterative least-square method for subspace tracking

Authors:
Shan Ouyang;Yingbo Hua
Affiliations:
Dept. of Commun. & Inf. Eng., Guilin Univ. of Electron. Technol., China;-
Venue:
IEEE Transactions on Signal Processing - Part II
Year:
2005

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Abstract

Subspace tracking is an adaptive signal processing technique useful for a variety of applications. In this paper, we introduce a simple bi-iterative least-square (Bi-LS) method, which is in contrast to the bi-iterative singular value decomposition (Bi-SVD) method. We show that for subspace tracking, the Bi-LS method is easier to simplify than the Bi-SVD method. The linear complexity algorithms based on Bi-LS are computationally more efficient than the existing linear complexity algorithms based on Bi-SVD, although both have the same performance for subspace tracking. A number of other existing subspace tracking algorithms of similar complexity are also compared with the Bi-LS algorithms.