• DocumentCode
    953498
  • Title

    A low-rank IE-QR algorithm for matrix compression in volume integral equations

  • Author

    Ozdemir, Nilufer A. ; Lee, Jin-Fa

  • Author_Institution
    ElectroScience Lab., Ohio State Univ., Columbus, OH, USA
  • Volume
    40
  • Issue
    2
  • fYear
    2004
  • fDate
    3/1/2004 12:00:00 AM
  • Firstpage
    1017
  • Lastpage
    1020
  • Abstract
    A single-level matrix compression algorithm based on pivoted QR factorization with partial matrix assembling, which exploits the rank deficiency of matrix blocks for physically separated groups of basis functions, is presented for the volume integral equation solution of electromagnetic scattering from arbitrarily shaped dielectric bodies. For a system of N equations, an amount of work of the order O(N2) has traditionally been required by the method of moments (MoM). The algorithm of the present paper reduces both computational complexity and storage requirement to O(N1.5) with relatively less dependence on the integral equation kernel. Hence, the proposed algorithm is more practical for large-scale problems and can be implemented in a wide range of applications with few or no modifications.
  • Keywords
    computational complexity; electromagnetic wave scattering; integral equations; matrix decomposition; method of moments; IE-QR algorithm; computational complexity; electromagnetic scattering; integral equation kernel; matrix blocks; matrix compression; method-of-moments; partial matrix assembling; pivoted QR factorization; storage requirement; volume integral equations; Assembly; Compression algorithms; Computational complexity; Dielectrics; Electromagnetic scattering; Integral equations; Kernel; Large-scale systems; Moment methods; Sampling methods;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/TMAG.2004.824575
  • Filename
    1284589