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Vermittelnde Ausgleichung Nach der Methode der Kleinsten Quadrate

ProzedurVermag
  • L. Molinari
Chapter
Part of the International Series of Numerical Mathematics book series (ISNM, volume 33)

Zusammenfassung

Die Prozedur vermag löst durch Schmidt’sche Orthogonalisierung das Minimumproblem:
$$||Fx + g|{|^2} + {e^2}||x|{|^2} = \sum\limits_1^n {{{\left( {\sum\limits_1^m {{f_{ij}}{x_j} + {g_i}} } \right)}^2} + {e^2}\sum {{x^2}_j + \min } } $$
.

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Literaturverzeichnis

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    Peters, G. und Wilkinson, J. H. 1970, The least squares problem and pseudo-inverses (The Computer Journal 13, 309–316.CrossRefGoogle Scholar
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    Golub, G. 1965, Numerical Method for Solving Least Squares Problems (Numerische Mathematik 7, 206–216).CrossRefGoogle Scholar
  3. [3]
    Rutishauser, H. 1968, Once again: The Least Squares Problem (Linear Algebra and its Applications 1, 479–488).CrossRefGoogle Scholar
  4. [4]
    Rice, John R. 1966, Experiments on Gram-Schmidt Orthogonalization (Math. Comp. 20, 325–328).CrossRefGoogle Scholar
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    Mazzario, A. 1973, Eine numerische Implementation der Gram-Schmidt-Orthogonalisation mit besonderer Berücksichtigung der Ritz-Iteration zur Berechnung von Eigenwerten (Dissertation ETH Nr. 5005).Google Scholar
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    Wilkinson, J. H. und Reinsch, C. 1971, Linear Algebra (Handbook of Automatic Computation II, Springer, Berlin-Heidelberg-New York, S. 134–150).Google Scholar

Copyright information

© Birkhäuser Verlag Basel 1977

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  • L. Molinari

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