The Art And Science Of Matrix Preconditioning-A Review

Abstract

The objective of this paper is to present a brief review of a number of techniques for matrix preconditioning. Preconditioners are almost always needed when solving large problem by using the Method of Moments (MoM) [1], since the matrices associated with such problems are often ill-conditioned, and iterative techniques such as the Conjugate Gradient and GMRES algorithms either fail to converge at all or are very slowly converging [2-11]. While a wide variety of preconditioners have been proposed by researchers in Matrix Methods to address the problem of slow convergence of ill-conditioned matrices, a 'magic bullet' that is robust enough to handle all types of ill-conditioned matrices has yet to be found. Consequently, this field is currently very active as a quick literature search will readily reveal.

Publication Date

10-11-2016

Publication Title

Call for Papers - ICCEM 2016: 2016 IEEE International Conference on Computational Electromagnetics

Number of Pages

17-19

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/COMPEM.2016.7588596

Socpus ID

84994670289 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84994670289

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