Electronic Resource
Springer
Numerische Mathematik
59 (1991), S. 561-580
ISSN:
0945-3245
Keywords:
65F20
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Summary We consider the following problem: Compute a vectorx such that ∥Ax−b∥2=min, subject to the constraint ∥x∥2=α. A new approach to this problem based on Gauss quadrature is given. The method is especially well suited when the dimensions ofA are large and the matrix is sparse. It is also possible to extend this technique to a constrained quadratic form: For a symmetric matrixA we consider the minimization ofx T A x−2b T x subject to the constraint ∥x∥2=α. Some numerical examples are given.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01385796
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