- Main
Bi-iterative least square method for subspace tracking
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-LSmethod 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 subspacetracking algorithms of similar complexity are also compared with the Bi-LS algorithms.
Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
Main Content
Enter the password to open this PDF file:
-
-
-
-
-
-
-
-
-
-
-
-
-
-