Results 71 to 80 of about 121 (92)
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2006
We give a theoretical explanation for the superlinear convergence behavior observed while solving large symmetric systems of equations using the Conjugate Gradient (CG) method or other Krylov subspace methods. We present a new bound on the relative error after n iterations. This bound is valid in an asymptotic sense, when the size N of the system grows
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We give a theoretical explanation for the superlinear convergence behavior observed while solving large symmetric systems of equations using the Conjugate Gradient (CG) method or other Krylov subspace methods. We present a new bound on the relative error after n iterations. This bound is valid in an asymptotic sense, when the size N of the system grows
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A survey of numerical linear algebra methods utilizing mixed-precision arithmetic
International Journal of High Performance Computing Applications, 2021Nicholas Higham +2 more
exaly
The loss of orthogonality in the Gram-Schmidt orthogonalization process
Computers and Mathematics With Applications, 2005Julien Langou, L Giraud
exaly
Numerical linear algebra for reconstruction inverse problems
Journal of Computational and Applied Mathematics, 2004Abdeljalil Nachaoui
exaly
Numerical Algorithms for Linear and Non linear Algebra
Lecture Notes in Computer Science, 2000Ulrich Rüede +2 more
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