Updating signal subspaces

Christian H. Bischof; Gautam M. Shroff

doi:10.1117/12.23490

1 November 1990 Updating signal subspaces

Christian H. Bischof, Gautam M. Shroff

Proceedings Volume 1348, Advanced Signal Processing Algorithms, Architectures, and Implementations; (1990) https://doi.org/10.1117/12.23490
Event: 34th Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1990, San Diego, CA, United States

Abstract

We develop an algorithm for adaptively estimating the noise subspace of a data matrix as is required in signal processing applications employing the ''signal subspace'' approach. The noise subspace is estimated using a rank-revealing QR factorization instead of the more expensive singular value or eigenvalue decompositions. Using incremental condition estimation to monitor the smallest singular values of triangular matrices we can update the rank-revealing triangular factorization inexpensively when new rows are added and old rows are deleted. Experiments demonstrate that the new approach usually requires 0(n2) work to update an n x n matrix and accurately tracks the noise subspace.

Citation Download Citation

Christian H. Bischof and Gautam M. Shroff "Updating signal subspaces", Proc. SPIE 1348, Advanced Signal Processing Algorithms, Architectures, and Implementations, (1 November 1990); https://doi.org/10.1117/12.23490

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