Thr formulation and analysis of numerical methods for inverse Eigenvalue problems
SIAM Journal on Numerical Analysis
An extended set of FORTRAN basic linear algebra subprograms
ACM Transactions on Mathematical Software (TOMS)
Numerical methods for inverse singular value problems3
SIAM Journal on Numerical Analysis
Introduction to parallel computing: design and analysis of algorithms
Introduction to parallel computing: design and analysis of algorithms
Using MPI: portable parallel programming with the message-passing interface
Using MPI: portable parallel programming with the message-passing interface
On the Least Squares Solution of Inverse Eigenvalue Problems
SIAM Journal on Numerical Analysis
ScaLAPACK user's guide
LAPACK Users' guide (third ed.)
LAPACK Users' guide (third ed.)
A Proposal for a Set of Parallel Basic Linear Algebra Subprograms
A Proposal for a Set of Parallel Basic Linear Algebra Subprograms
LAPACK Working Note 37: Two Dimensional Basic Linear Algebra Communication Subprograms
LAPACK Working Note 37: Two Dimensional Basic Linear Algebra Communication Subprograms
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
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In this paper we propose two algorithms for solving the Inverse Additive Singular Value Problem (IASVP). The first one, denoted MI, solves the IASVP by formulating it like a nonlinear problem and using a Newton type method. MI is a local convergent algorithm. The second one, called LP, solves the IASVP by formulating it as a least squares problem and using a projection method; LP is a global convergent method. We present the sequential and parallel versions for each algorithm, and we show numerical experiments to illustrate their behaviour and good performance.