Verification of Positive Definiteness |
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Authors: | S.M. Rump |
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Affiliation: | (1) Institute for Reliable Computing, Hamburg University of Technology, Schwarzenbergstr. 95, 21071 Hamburg, Germany;(2) Faculty of Science and Engineering, Waseda University, 2-4-12 Okubo, Shinjuku-ku, Tokyo 169–0072, Japan |
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Abstract: | We present a computational, simple and fast sufficient criterion to verify positive definiteness of a symmetric or Hermitian matrix. The criterion uses only standard floating-point operations in rounding to nearest, it is rigorous, it takes into account all possible computational and rounding errors, and is also valid in the presence of underflow. It is based on a floating-point Cholesky decomposition and improves a known result. Using the criterion an efficient algorithm to compute rigorous error bounds for the solution of linear systems with symmetric positive definite matrix follows. A computational criterion to verify that a given symmetric or Hermitian matrix is not positive definite is given as well. Computational examples demonstrate the effectiveness of our criteria. AMS subject classification (2000) 65G20, 15A18 |
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Keywords: | positive definite verification self-validating methods Cholesky decomposition rigorous error bounds INTLAB semidefinite programming |
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