• DocumentCode
    2287570
  • Title

    Solving least squares problems by neural network approach

  • Author

    Zhong, Fan ; Lisheng, Tian

  • Author_Institution
    Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
  • fYear
    1994
  • fDate
    13-16 Apr 1994
  • Firstpage
    539
  • Abstract
    In this paper, a neural network approach to least squares (LS) problems is proposed. The linear LS problems are solved by using a class of neural network rather than by other conventional methods (such as SVD, Householder transform, etc.). The theoretical analysis and computer simulations show that the method is efficient and reliable, and it is computationally simple and has a normal structure
  • Keywords
    least squares approximations; mathematics computing; neural nets; optimisation; computer simulations; linear least squares problems; mathematics computing; neural network; parallel computation; Analytical models; Cost function; Equations; Least squares methods; Neural networks; Optimization methods; Reliability theory; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Speech, Image Processing and Neural Networks, 1994. Proceedings, ISSIPNN '94., 1994 International Symposium on
  • Print_ISBN
    0-7803-1865-X
  • Type

    conf

  • DOI
    10.1109/SIPNN.1994.344855
  • Filename
    344855