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Matrices, Norms, and Condition Numbers

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Scientific Data Analysis
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Abstract

Matrix notation greatly facilitates the theoretical discussion of overdeter- mined systems, although the actual computational steps are often more effectively implemented by other means. Matrices are so familiar that to present a definition of them seems unduly formal, almost a waste of time. Nevertheless, for the sake of completeness we give a definition. A matrix is an array of mn elements, arranged in m rows and n columns

$$A = \left( {\begin{array}{*{20}{c}} {{a_{11}}}&{{a_{12}}}& \cdots &{{a_{1n}}} \\ {{a_{21}}}&{{a_{22}}}& \cdots &{{a_{2n}}} \\ \vdots & \vdots &{}& \vdots \\ {{a_{m1}}}&{{a_{m2}}}&{}&{{a_{mn}}} \end{array}} \right).$$
((2.1))

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© 1990 Springer-Verlag New York Inc.

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Branham, R.L. (1990). Matrices, Norms, and Condition Numbers. In: Scientific Data Analysis. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3362-6_2

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  • DOI: https://doi.org/10.1007/978-1-4612-3362-6_2

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7981-5

  • Online ISBN: 978-1-4612-3362-6

  • eBook Packages: Springer Book Archive

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