Results 241 to 250 of about 203,139 (278)

Euclidean Norm Minimization of the SOR Operators

SIAM Journal on Matrix Analysis and Applications, 1998
The spectral norm is an asymptotic measure of the rate of convergence of a linear iterative method for solving linear systems. \textit{G. H. Golub} and \textit{J. dePillis} [Toward an effective two-parameter method, in Iterative Methods for Large Linear Systems, Academic press, New York (1990)] have raised the question of determing, for each \(k\geq 1\)
Apostolos Hadjidimos, Michael Neumann
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On Euclidean Norm Balancing

PAMM, 2013
AbstractWe recall Euclidean norm balancing of linear time‐invariant control systems and extend it to other classes of systems. (© 2013 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Tobias Damm, Luc N. Muhirwa
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Normed and Euclidean Spaces

2020
In this chapter we discuss some basic geometric and topological properties of normed and Euclidean spaces, which are the most important types of spaces of functional analysis.
Vladimir I. Bogachev, Oleg G. Smolyanov
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Euclidean-Norm Error Bounds for SYMMLQ and CG

SIAM Journal on Matrix Analysis and Applications, 2019
Summary: For positive definite and semidefinite consistent \(Ax_\star=b\), we use the Gauss-Radau approach of \textit{G. H. Golub} and \textit{G. Meurant} [BIT 37, No. 3, 687--705 (1997; Zbl 0888.65050)] to obtain an upper bound on the error \(\|x_\star-x_k^L\|_2\) for SYMMLQ iterates, assuming exact arithmetic.
Ron Estrin, Dominique Orban, Michael A. Saunders   +2 more
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Linear combination of norms in improving approximation of Euclidean norm

Pattern Recognition Letters, 2013
In the past, different distance functions and their combinations had been proposed as good approximators of Euclidean metrics. In particular in recent years, a few distance functions with their general forms in n-dimensional real and integer spaces were identified for their improved performances in approximating corresponding Euclidean metrics. In this
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Euclidean Sections of Direct Sums of Normed Spaces

Canadian Mathematical Bulletin, 2003
AbstractWe study the dimension of “random” Euclidean sections of direct sums of normed spaces. We compare the obtained results with results from [LMS], to show that for the direct sums the standard randomness with respect to the Haar measure on Grassmanian coincides with a much “weaker” randomness of “diagonal” subspaces (Corollary 1.4 and explanation ...
Litvak, A. E., Milman, V. D.
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An Efficient Algorithm for Minimizing a Sum of Euclidean Norms with Applications

SIAM Journal on Optimization, 1997
Summary: In recent years rich theories on polynomial-time interior-point algorithms have been developed. These theories and algorithms can be applied to many nonlinear optimization problems to yield better complexity results for various applications. In this paper, the problem of minimizing a sum of Euclidean norms is studied.
Guoliang Xue, Yinyu Ye 0001
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A simple geometry of Euclidean norms

IEEE Transactions on Education, 1988
A simple two-dimensional geometry is presented for the Euclidean norm of a vector with any number of components. The proposed geometrical construction is an n-sided right triangle whose sides are the component elements of the vector. >
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A Smoothing Newton Method for Minimizing a Sum of Euclidean Norms

SIAM Journal on Optimization, 2000
Summary: We consider the problem of minimizing a sum of Euclidean norms, \(f(x) = \sum_{i=1}^m\|b_i - A_i^Tx \|\). This problem is a nonsmooth problem because \(f\) is not differentiable at a point \(x\) when one of the norms is zero. In this paper we present a smoothing Newton method for this problem by applying the smoothing Newton method proposed by
Liqun Qi 0001, Guanglu Zhou
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Quadratic number fields that are euclidean but not norm-euclidean

2009
Diese Diplomarbeit befasst sich mit quadratischen Zahlkörpern welche euklidisch aber nicht normeuklidisch sind.
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