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Titlebook: Iterative Solution of Large Sparse Systems of Equations; Wolfgang Hackbusch Book 19941st edition Springer-Verlag New York, Inc. 1994 Canon

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书目名称Iterative Solution of Large Sparse Systems of Equations
编辑Wolfgang Hackbusch
视频video
丛书名称Applied Mathematical Sciences
图书封面Titlebook: Iterative Solution of Large Sparse Systems of Equations;  Wolfgang Hackbusch Book 19941st edition Springer-Verlag New York, Inc. 1994 Canon
出版日期Book 19941st edition
关键词Canon; DEX; Fourier analysis; Jacobi method; Matrix; algebra; boundary element method; construction; correla
版次1
doihttps://doi.org/10.1007/978-1-4612-4288-8
isbn_softcover978-1-4612-8724-7
isbn_ebook978-1-4612-4288-8Series ISSN 0066-5452 Series E-ISSN 2196-968X
issn_series 0066-5452
copyrightSpringer-Verlag New York, Inc. 1994
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Wolfgang Hackbuschker werdenden Internationalisierung der Hochschulen und Studiengänge im deutschsprachigen Raum gewinnt dieser Aspekt an Bedeutung. Gegenüber herkömmlichen AbsolventInnenstudien, die überwiegend auf quantitativen Analysen basieren, wird hier ein Mixed-Methods-Ansatz verwendet, um eine breitere und be
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Iterative Methods,nd the given system of equations, as well as ., guaranteeing the success of the iteration. The most important result of this chapter is the characterisation of the convergence of linear iterations by the spectral radius of the iteration matrix (cf. §3.1.3). Since we consider iterative methods for sy
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,Methods of Jacobi and Gauß-Seidel and SOR Iteration in the Positive Definite Case,er, is essentially different for the case of positive definite matrices . discussed below and other cases studied in §§5–6. The introductory Section 4.1 underlines the fact that the positive definite case is of practical interest: The Poisson-model matrix is positive definite. Chapter 4.2 is a recap
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Transformations, Secondary Iterations, Incomplete Triangular Decompositions,ucing new features. Techniques of the former kind are the transformations described in §§8.1–3 and the composed methods from §8.4 generated by a secondary iteration, whereas the ILU decomposition from §8.5 is of the latter kind, since it produces a new method.
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