• DocumentCode
    1234313
  • Title

    A survey of conjugate gradient algorithms for solution of extreme eigen-problems of a symmetric matrix

  • Author

    Yang, X. ; Sarkar, T.K. ; Arvas, E.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Syracuse Univ., NY, USA
  • Volume
    37
  • Issue
    10
  • fYear
    1989
  • Firstpage
    1550
  • Lastpage
    1556
  • Abstract
    A survey of various conjugate gradient (CG) algorithms is presented for the minimum/maximum eigen-problems of a fixed symmetric matrix. The CG algorithms are compared to a commonly used conventional method found in IMSL. It is concluded that the CG algorithms are more flexible and efficient than some of the conventional methods used in adaptive spectrum analysis and signal processing.<>
  • Keywords
    eigenvalues and eigenfunctions; matrix algebra; signal processing; spectral analysis; adaptive signal processing; adaptive spectrum analysis; conjugate gradient algorithms; extreme eigen-problems; maximum eigenvalue; minimum eigenvalue; symmetric matrix; Adaptive signal processing; Algorithm design and analysis; Character generation; Computational complexity; Covariance matrix; Eigenvalues and eigenfunctions; Iterative algorithms; Iterative methods; Signal processing algorithms; Symmetric matrices;
  • fLanguage
    English
  • Journal_Title
    Acoustics, Speech and Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0096-3518
  • Type

    jour

  • DOI
    10.1109/29.35393
  • Filename
    35393
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1234313