The development of ARPACK began as a research code written in Matlab and then in
Fortran 77 in 1990. Initially, the code was developed to study and verify the properties of the …

Among the iterative methods for solving large linear systems with a sparse (or, possibly,
structured) nonsymmetric matrix, those that are based on the Lanczos process feature short …

It is trite but true to say that research on the symmetric eigenvalue problem has flourished
since the first edition of this book appeared in 1980. I had dreamed of including the …

In many large scale scientific or engineering computations, ranging from computing the
frequency response of a circuit to the earthquake response of a buildingto the energy levels …

This book, Eigensystems, is the second volume in a projected five-volume series entitled
Matrix Algorithms. The first volume treated basic decompositions. The three following this …

Numerical Linear Algebra and Applications, 2nd Edition: Back Matter Page 1 page 501 i i i i
Bibliography E. Anderson, Z. Bai, C. Bischof, S. Blackford, J. Demmel, J. Dongarra, J. Du …

This book, Basic Decompositions, is the first volume in a projected five-volume series
entitled Matrix Algorithms. The other four volumes will treat eigensystems, iterative methods …

An “industrial strength” algorithm for solving sparse symmetric generalized eigenproblems is
described. The algorithm has its foundations in known techniques in solving sparse …

We present four numerical methods for computing the singular value decomposition (SVD)
of large sparse matrices on a multiprocessor architecture. We emphasize Lanczos and …

The purpose of this book is to unify and document in one place many of the techniques and
much of the current understanding about solving systems of linear equations on vector and …