Titlebook: Computational Methods for General Sparse Matrices; Zahari Zlatev Book 1991 Springer Science+Business Media B.V. 1991 Mathematica.Matrix.al

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https://doi.org/10.1057/9780230613188rge and sparse linear least squares problems. Two implementations of the Givens plane rotations for large and sparse linear least squares problems were discussed in the previous chapter. In the present chapter some pivotal strategies that can successfully be used with the second implementation will

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https://doi.org/10.1007/978-1-349-73900-4mation to x = A.b = (A.A).A.b is to be calculated. In this chapter it will be shown that this problem can be transformed into an equivalent problem, which is a system of linear algebraic equations Cy=d whose coefficient matrix C is symmetric and positive definite. Moreover, C can be written as C = D

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Sparse Matrix Technique for Ordinary Differential Equations,ix technique is a very useful option in a package for solving such systems numerically. Such an option, the code . is described in this chapter. . is written for systems of ., but the same ideas can be applied to systems of non-linear ..

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Orthogonalization Methods,umns (Q.Q=I, I being the identity matrix in R.), D ∈ .. is a diagonal matrix and R ∈ .. is an upper triangular matrix. Very often matrix D is the identity matrix and if this is so, then (12.1) is reduced to

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Overview: 978-90-481-4086-2978-94-017-1116-6

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