An Improved Arc Algorithm for Detecting Definite Hermitian Pairs
A 25-year-old and somewhat neglected algorithm of Crawford and Moon attempts to determine whether a given Hermitian matrix pair (A, B) is definite by exploring the range of the function ..., which is a subset of the unit circle. The researchers revisit the algorithm and show that with suitable modif...
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| Published in | SIAM journal on matrix analysis and applications Vol. 31; no. 3; pp. 1131 - 1151 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Philadelphia, PA
Society for Industrial and Applied Mathematics
01.01.2009
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0895-4798 1095-7162 |
| DOI | 10.1137/08074218X |
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| Abstract | A 25-year-old and somewhat neglected algorithm of Crawford and Moon attempts to determine whether a given Hermitian matrix pair (A, B) is definite by exploring the range of the function ..., which is a subset of the unit circle. The researchers revisit the algorithm and show that with suitable modifications and careful attention to implementation details it provides a reliable and efficient means of testing definiteness. A clearer derivation of the basic algorithm is given that emphasizes an arc expansion viewpoint and makes no assumptions about the definiteness of the pair. Convergence of the algorithm is proved for all (A, B), definite or not. It is shown that proper handling of three details of the algorithm is crucial to the efficiency and reliability: how the midpoint of an arc is computed, whether shrinkage of an arc is permitted, and how directions of negative curvature are computed.(ProQuest: ... denotes formulae/symbols omitted.) |
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| AbstractList | A 25-year-old and somewhat neglected algorithm of Crawford and Moon attempts to determine whether a given Hermitian matrix pair (A, B) is definite by exploring the range of the function ..., which is a subset of the unit circle. The researchers revisit the algorithm and show that with suitable modifications and careful attention to implementation details it provides a reliable and efficient means of testing definiteness. A clearer derivation of the basic algorithm is given that emphasizes an arc expansion viewpoint and makes no assumptions about the definiteness of the pair. Convergence of the algorithm is proved for all (A, B), definite or not. It is shown that proper handling of three details of the algorithm is crucial to the efficiency and reliability: how the midpoint of an arc is computed, whether shrinkage of an arc is permitted, and how directions of negative curvature are computed.(ProQuest: ... denotes formulae/symbols omitted.) |
| Author | Tisseur, Françoise Guo, Chun-Hua Higham, Nicholas J. |
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| Keywords | Saddle point method Modification Costs Hermitian generalized eigenvalue problem Linear form Unit circle Shrinkage estimator Hermitian matrix hyperbolic quadratic eigenvalue problem Polynomial method Computing saddle point linear system Partial differential equation Implementation Convergence 15A18 Statistical test Efficiency Cholesky method 65F30 Crawford number 65F15 Eigenvalue problem Mathematical expansion Expansion Conjugate gradient method definite pair direction of negative curvature Polynomial matrix pencil Algorithm Factorization Saddle point Numerical analysis Linear system Linear algebra Hyperbolic equation Matrix method Matrix polynomial Reliability Curvature |
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| SubjectTerms | Algebra Algorithms Applications Computational efficiency Convergence Curvature Derivation Exact sciences and technology Linear and multilinear algebra, matrix theory Mathematical analysis Mathematics Moon Numerical analysis Numerical analysis. Scientific computation Numerical linear algebra Probability and statistics Probability theory and stochastic processes Reliability, life testing, quality control Sciences and techniques of general use Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications) Statistics Symbols |
| Title | An Improved Arc Algorithm for Detecting Definite Hermitian Pairs |
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