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ETNA - Electronic Transactions on Numerical Analysis
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Verlag der Österreichischen Akademie der Wissenschaften Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at |
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DATUM, UNTERSCHRIFT / DATE, SIGNATURE
BANK AUSTRIA CREDITANSTALT, WIEN (IBAN AT04 1100 0006 2280 0100, BIC BKAUATWW), DEUTSCHE BANK MÜNCHEN (IBAN DE16 7007 0024 0238 8270 00, BIC DEUTDEDBMUC)
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ETNA - Electronic Transactions on Numerical Analysis, pp. 197-206, 2018/02/13
Matrix functions of the form $f(A)v$, where $A$ is a large symmetric matrix, $f$ is afunction, and $v\\ne 0$ is a vector, are commonly approximated by first applying a few,say $n$, steps of the symmetric Lanczos process to $A$ with the initial vector $v$ in order todetermine an orthogonal section of $A$. The latter is represented by a (small)$n\\times n$ tridiagonal matrix to which $f$ is applied. This approach uses the $n$ firstLanczos vectors provided by the Lanczos process. However, $n$ steps of the Lanczosprocess yield $n+1$ Lanczos vectors. This paper discusses how the $(n+1)$stLanczos vector can be used to improve the quality of the computed approximation of$f(A)v$. Also the approximation of expressions of the form $v^Tf(A)v$ is considered.
Keywords: matrix function, symmetric Lanczos process, Gauss quadrature