Large Scale Eigenvalue ProblemsEdited By
- J. Cullum
- R.A. Willoughby
Results of research into large scale eigenvalue problems are presented in this volume. The papers fall into four principal categories:novel algorithms for solving large eigenvalue problems, novel computer architectures, computationally-relevant theoretical analyses, and problems where large scale eigenelement computations have provided new insight.
North-Holland Mathematics Studies
Published: January 1986
All the papers are by well-known specialists, which makes the book very attractive for researchers in the field and those involved in practical computation of large scale eigenvalue problems.
Mathematics and Computers in Simulation
- High Performance Computers and Algorithms from Linear Algebra (J.J. Dongarra, D.C. Sorensen). The Impact of Parallel Architectures on the Solution of Eigenvalue Problems (I.C.F. Ipsen, Y. Saad). Computing the Singular Value Decomposition on a Ring of Array Processors (C. Bischof, C. Van Loan). Quantum Dynamics with the Recursive Residue Generation Method: Improved Algorithm for Chain Propagators (R.E. Wyatt, D.S. Scott). Eigenvalue Problems and Algorithms in Structural Engineering (R.G. Grimes, J.G. Lewis, H.D. Simon). A Generalised Eigenvalue Problem and the Lanczos Algorithm (T. Ericsson). Numerical Path Following and Eigenvalue Criteria for Branch Switching (Y.F. Zhou, A. Ruhe). The Lanczos Algorithm in Molecular Dynamics: Calculation of Spectral Densities (G. Moro, J.H. Freed). Investigation of Nuclear Dynamics in Molecules by Means of the Lanczos Algorithm (E. Haller, H. Köppel). Examples of Eigenvalue/Vector Use in Electric Power System Problems (J.E. Van Ness). A Practical Procedure for Computing Eigenvalues of Large Sparse Nonsymmetric Matrices (J. Cullum, R.A. Willoughby). Computing the Complex Eigenvalue Spectrum for Resistive Magnetohydrodynamics (W. Kerner). Ill Conditioned Eigenproblems (F. Chatelin). Stably Computing the Kronecker Structure and Reducing Subspaces of Singular Pencils A - &pgr;B for Uncertain Data (J. Demmel, B. Kågström). Index.