Infinity norm bounds for the inverse of Nekrasov matrices using scaling matrices
Resumen: 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.
Idioma: Inglés
DOI: 10.1016/j.amc.2019.04.027
Año: 2019
Publicado en: Applied Mathematics and Computation 358 (2019), 119-127
ISSN: 0096-3003

Factor impacto JCR: 3.472 (2019)
Categ. JCR: MATHEMATICS, APPLIED rank: 7 / 260 = 0.027 (2019) - Q1 - T1
Factor impacto SCIMAGO: 0.969 - Computational Mathematics (Q1) - Applied Mathematics (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MICINN/MTM2015-65433-P
Tipo y forma: Article (PostPrint)
Área (Departamento): Área Matemática Aplicada (Dpto. Matemática Aplicada)

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