Abstract
Computing a few eigenpairs of large-scale matrices is a significant problem in science and engineering applications and a very active area of research. In this paper, two methods that compute extreme eigenpairs of positive-definite matrix pencils are combined into a hybrid scheme that inherits the advantages of both constituents. The hybrid algorithm is developed and analyzed in the framework of model-based methods for trace minimization.
This work was supported by NSF Grants ACI0324944 and CCR9912415, and by the School of Computational Science of Florida State University.
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Keywords
- Conjugate Gradient Method
- Outer Iteration
- Superlinear Convergence
- Generalize Eigenvalue Problem
- Matrix Pencil
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Absil, P.A., Baker, C.G., Gallivan, K.A., Sameh, A. (2005). Adaptive Model Trust Region Methods for Generalized Eigenvalue Problems. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J.J. (eds) Computational Science – ICCS 2005. ICCS 2005. Lecture Notes in Computer Science, vol 3514. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428831_5
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DOI: https://doi.org/10.1007/11428831_5
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