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- W22441479 abstract "Publisher Summary This chapter presents a novel algorithm for updating the singular value decomposition (SVD) in parallel. It is an improvement of a Jacobi-type SVD updating algorithm, where now the exact orthogonality of the matrix of short singular vectors is guaranteed by means of a minimal factorization in terms of angles. Its orthogonality is known to be crucial for the numerical stability of the overall algorithm. The factored approach has advantages with respect to parallel implementation. The chapter derives a triangular array of rotation cells, performing an orthogonal matrix-vector multiplication, and a modified Jacobi array for SVD updating. Both arrays can be built with CORDIC processors since the algorithms make exclusive use of Givens rotations." @default.
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- W22441479 date "1995-01-01" @default.
- W22441479 modified "2023-09-27" @default.
- W22441479 title "Stable jacobi svd updating by factorization of the orthogonal matrix" @default.
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- W22441479 doi "https://doi.org/10.1016/b978-044482107-2/50027-3" @default.
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