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# By how much can Residual Minimization Accelerate the Convergence of Orthogonal Residual Methods?

1. SYS LBL 0404252 ` ` 00000nam^^22^^^^^^^^450 ` ` 20200403122659.7 ` ` \$a 000172675300005 \$2 WOS ` ` \$a 0035602327 \$2 SCOPUS `70` \$a 10.1023/A:1011889705659 \$2 DOI `0-` \$a eng \$d eng ` ` \$a NL `1-` \$a By how much can Residual Minimization Accelerate the Convergence of Orthogonal Residual Methods? ` ` \$a 25 s. `-1` \$1 001 cav_un_epca*0254541 \$1 011 \$a 1017-1398 \$1 200 1 \$a Numerical Algorithms \$v Roč. 27, - (2001), s. 189-213 `1-` \$a system of linear algebraic equations `1-` \$a iterative method `1-` \$a Krylov space method `1-` \$a conjugate gradient method `1-` \$a biconjugate gradient method `1-` \$a CG `1-` \$a CGNE `1-` \$a CGNR `1-` \$a CGS `1-` \$a FOM `1-` \$a GMRes `1-` \$a QMR `1-` \$a TFQMR `1-` \$a residual smoothing `1-` \$a MR smoothing `1-` \$a QMR smoothing `-1` \$3 cav_un_auth*0207700 \$a Gutknecht \$b M. H. \$y CH \$4 070 `-1` \$3 cav_un_auth*0100819 \$a Rozložník \$b Miroslav \$p UIVT-O \$w Department of Computational Mathematics \$4 070 \$o Department of Computational Methods \$T Ústav informatiky AV ČR, v. v. i.

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