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Applied Mathematics and ComputationVolume 284, 5 July 2016, Pages 12-23

Euclidean norm estimates of the inverse of some special block matrices(Article)

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  • aDepartment of Mathematics and Informatics, Faculty of Science, University of Novi Sad, Trg D. Obradovića 4, Novi Sad, 21000, Serbia
  • bFaculty of Technical Sciences, University of Novi Sad, Trg D. Obradovića 6, Novi Sad, 21000, Serbia

Abstract

In this paper we start from the known lower bounds for minimal singular value of the matrices possessing certain kind of the diagonal dominance property, and derive Euclidean norm estimates of the inverses of several new subclasses of the block H-matrices. The motivation comes from applications where the matrix in question has distinguished block structure, which can be exploited to obtain useful information. An example arising from ecological modeling illustrates the benefits of the presented approach. © 2016 Elsevier B.V. All rights reserved.

Author keywords

Block matricesEuclidean matrix normInverse matrix

Indexed keywords

Engineering controlled terms:Inverse problems
Engineering uncontrolled termsBlock H-matricesBlock matricesBlock structuresDiagonal dominanceEcological modelingEuclidean matrixInverse matrixSingular values
Engineering main heading:Matrix algebra

Funding details

Funding sponsor Funding number Acronym
Ministry of Science and Environmental Protection174019
Provincial Secretariat for Science and Technological Development0851PSSTD

  • 1

    The authors wish to thank anonymous referees whose comments improved the quality of presented results. This work is partly supported by the Ministry of Science and Environmental Protection of Serbia, Grant 174019 and by the Provincial Secretariat of Science and Technological Development of Vojvodina, Serbia , Grant 0851 .

  • ISSN: 00963003
  • CODEN: AMHCB
  • Source Type: Journal
  • Original language: English
  • DOI: 10.1016/j.amc.2016.02.048
  • Document Type: Article
  • Publisher: Elsevier Inc.

  Cvetković, L.; Department of Mathematics and Informatics, Faculty of Science, University of Novi Sad, Trg D. Obradovića 4, Novi Sad, Serbia;
© Copyright 2017 Elsevier B.V., All rights reserved.

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