Computing a matrix symmetrizer exactly using modified multiple modulus residue arithmetic (Q1097642)
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scientific article; zbMATH DE number 4034997
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Computing a matrix symmetrizer exactly using modified multiple modulus residue arithmetic |
scientific article; zbMATH DE number 4034997 |
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Computing a matrix symmetrizer exactly using modified multiple modulus residue arithmetic (English)
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1988
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A multiple-modulus residue arithmetic is introduced and applied to computing an error-free matrix symmetrizer (i.e., a symmetric nonsingular X satisfying \(XA=A\) tX). In particular, when \(A=(a_{ij})\) is a lower Hessenberg matrix, with nonzero codiagonal elements, then the method recovers the following simple and elegant recursive algorithm to compute a symmetrizer, suggested by Datta (unpublished): Let x 1,x 2,...,x n be the rows of a symmetrizer X to be computed. Step 1: Choose \(x\quad n=(\alpha,0,...,0),\) where \(\alpha\neq 0\) is arbitrary; Step 2 Compute \(x^{n-1},x^{n-2},...,x\) 1 recursively from \(x\quad i=(1/a_{i,i+1})\times (x^{i+1}A-a_{i+1,i+1}x^{i+1}-a_{i+2,\quad i+1}x^{i+2}-...-a_{n,i+1}x\quad n),\) \(i=n-1,...,1\); Step 3: Print x 1,x 2,...,x n and stop.
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Euclid's algorithm
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Gauss elimination
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similar matrices
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non-symmetric eigenvalue problem
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floating-point modular arithmetic
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multiple-modulus residue arithmetic
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error-free matrix symmetrizer
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recursive algorithm
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0.86527884
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0.8637306
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0.86355877
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0.8575383
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0.85482705
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0.8521935
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0.84563196
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