Infinity norm bounds for the inverse of Nekrasov matrices using scaling matrices

H. Orera and J.M. Peña

Applied Mathematics and Computation, 2019, vol. 358, issue C, 119-127

Abstract: For many applications, it is convenient to have good upper bounds for the norm of the inverse of a given matrix. In this paper, we obtain such bounds when A is a Nekrasov matrix, by means of a scaling matrix transforming A into a strictly diagonally dominant matrix. Numerical examples and comparisons with other bounds are included. The scaling matrices are also used to derive new error bounds for the linear complementarity problems when the involved matrix is a Nekrasov matrix. These error bounds can improve considerably other previous bounds.

Keywords: Infinity matrix norm; Inverse matrix; Nekrasov matrices; H-matrices; Strictly diagonally dominant matrices; Scaling matrix (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:358:y:2019:i:c:p:119-127

DOI: 10.1016/j.amc.2019.04.027

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