Bidiagonal SVD Computation via an Associated Tridiagonal Eigenproblem
Bidiagonal SVD Computation via an Associated Tridiagonal Eigenproblem
The Singular Value Decomposition (SVD) is widely used in numerical analysis and scientific computing applications, including dimensionality reduction, data compression and clustering, and computation of pseudo-inverses. In many cases, a crucial part of the SVD of a general matrix is to find the SVD of an associated bidiagonal matrix. This …