SIAM Journal on Matrix Analysis and Applications · 2004 · 60 citations · 15 references
ComputingComputer ScienceAlgorithmsComputational MechanicsScientific ComputingEigenvalue ProblemsMatrix ComputationNumerical AlgorithmsNumerical AnalysisNumerical Linear AlgebraNumerical Methods For Differential EquationsCorrection EquationsEigenvalue AlgorithmsEigenvalue ComputationMatrix Eigenvalue Problems
Abstract. We present a new numerical method for computing selected eigenvalues and eigenvectors of the two-parameter eigenvalue problem. The method does not require good initial approximations and is able to tackle large problems that are too expensive for methods that compute all eigenvalues. The new method uses a two-sided approach and is a generalization of the Jacobi– Davidson type method for right definite two-parameter eigenvalue problems [M. E. Hochstenbach and B. Plestenjak, SIAM J. Matrix Anal. Appl., 24 (2002), pp. 392–410]. Here we consider the much wider class of nonsingular problems. In each step we first compute Petrov triples of a small projected two-parameter eigenvalue problem and then expand the left and right search spaces using approximate solutions to appropriate correction equations. Using a selection technique, it is possible to compute more than one eigenpair. Some numerical examples are presented. Key words. two-parameter eigenvalue problem, subspace method, Jacobi–Davidson method, correction equation, Petrov–Galerkin, two-sided approach
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Mathematics and Computers in Simulation · 1991 · 2.5K citations
Eigenvalues of the Laplacian in Two Dimensions
J.R. Kuttler, V. G. Sigillito · SIAM Review · 1984 · 243 citations
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Tyler Seacrest, Weiqing Gu · 2005 · 194 citations