• DocumentCode
    1056174
  • Title

    Regularized image reconstruction using SVD and a neural network method for matrix inversion

  • Author

    Steriti, Ronald J. ; Fiddy, Michael A.

  • Author_Institution
    Dept. of Electr. Eng., Massachusetts Univ., Lowell, MA, USA
  • Volume
    41
  • Issue
    10
  • fYear
    1993
  • fDate
    10/1/1993 12:00:00 AM
  • Firstpage
    3074
  • Lastpage
    3077
  • Abstract
    Two methods of matrix inversion are compared for use in an image reconstruction algorithm. The first is based on energy minimization using a Hopfield neural network. This is compared with the inverse obtained using singular value decomposition (SVD). It is shown for a practical example that the neural network provides a more useful and robust matrix inverse
  • Keywords
    Hopfield neural nets; image reconstruction; inverse problems; matrix algebra; Hopfield neural network; SVD; energy minimization; image reconstruction; matrix inversion; regularisation technique; robust matrix inverse; singular value decomposition; Discrete Fourier transforms; Frequency estimation; Hopfield neural networks; Image reconstruction; Matrices; Matrix decomposition; Neural networks; Productivity; Robustness; Singular value decomposition;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.277813
  • Filename
    277813