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Titlebook: Handbook for Automatic Computation; Volume II: Linear Al J. H. Wilkinson,C. Reinsch,F. L. Bauer,A. S. House Book 1971 Springer-Verlag Berli

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Solution of Symmetric and Unsymmetric Band Equations and the Calculations of Eigenvectors of Band MaIn an earlier paper in this series [2] the triangular factorization of positive definite band matrices was discussed. With such matrices there is no need for pivoting, but with non-positive definite or unsymmetric matrices pivoting is necessary in general, otherwise severe numerical instability may result even when the matrix is well-conditioned.
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Solution of Real and Complex Systems of Linear EquationsIf . is a non-singular matrix then, in general, it can be factorized in the form . = ., where . is lower-triangular and . is upper-triangular. The factorization, when it exists, is unique to within a non-singular diagonal multiplying factor.
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Linear Least Squares Solutions by Housholder TransformationsLet . be a given .×. real matrix with .≧. and of rank . and . a given vector. We wish to determine a vector . such that.where ∥ … ∥ indicates the euclidean norm. Since the euclidean norm is unitarily invariant.where .=.. and ... = .. We choose . so that.and . is an upper triangular matrix. Clearly,.where . denotes the first . components of ..
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The Jacobi Method for Real Symmetric MatricesAs is well known, a real symmetric matrix can be transformed iteratively into diagonal form through a sequence of appropriately chosen . (in the following called .):.where ..= ..(.) is an orthogonal matrix which deviates from the unit matrix only in the elements
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The Implicit , AlgorithmIn [1] an algorithm was described for carrying out the . algorithm for a real symmetric matrix using shifts of origin. This algorithm is described by the relations.where .. is orthogonal, .. is lower triangular and .. is the shift of origin determined from the leading 2×2 matrix of ...
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978-3-642-86942-6Springer-Verlag Berlin Heidelberg 1971
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