• DocumentCode
    3443268
  • Title

    The Algorithm of Neural Networks on the Initial Value Problems in Ordinary Differential Equations

  • Author

    Li-Ying, Xu ; Hui, Wen ; Zhe-Zhao, Zeng

  • Author_Institution
    Changsha Univ. of Sci. & Technol., Changsha
  • fYear
    2007
  • fDate
    23-25 May 2007
  • Firstpage
    813
  • Lastpage
    816
  • Abstract
    A new method for solving initial value problems in ordinary differential equations (ODES) is proposed in this paper. The algorithm of neural networks based on the cosine basis functions is studied in detail. The convergence theorem of neural networks algorithm is given and proved. The algorithm is validated by the simulation examples of ODES. The results show the proposed approach is more precise than modified Euler method and Heun´s method.
  • Keywords
    differential equations; initial value problems; neural nets; Heun method; convergence theorem; cosine basis functions; initial value problems; modified Euler method; neural networks; ordinary differential equations; Differential equations; Industrial electronics; Neural networks; Cosine Basis Functions; Neural Network; Ordinary Differential Equations; convergence theorem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-0737-8
  • Electronic_ISBN
    978-1-4244-0737-8
  • Type

    conf

  • DOI
    10.1109/ICIEA.2007.4318520
  • Filename
    4318520
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3443268