• DocumentCode
    2329975
  • Title

    Emulated digital CNN-UM implementation of a barotropic ocean model

  • Author

    Nagy, Zoltán ; Szolgay, Péter

  • Author_Institution
    Dept. of Image Process. & Neurocomput., Veszprem Univ., Hungary
  • Volume
    4
  • fYear
    2004
  • fDate
    25-29 July 2004
  • Firstpage
    3137
  • Abstract
    The solution of partial differential equations (PDE) has long been one of the most important fields of mathematics, due to the frequent occurrence of spatio-temporal dynamics in many branches of physics, engineering and other sciences. One of the most exciting area is the simulation of compressible and incompressible fluids which appears in many important applications in aerodynamics, meteorology and oceanography. On the other hand the solution of these equations requires enormous computing power. In this paper a CNN-UM simulation of ocean currents is presented. Unfortunately the non-linearity of the governing equations does not make possible to utilize the huge computing power of the analog CNN-UM chips. To improve the performance of our solution an emulated digital CNN-UM is used where the cell model of the architecture is modified to handle the non-linearity of the model.
  • Keywords
    cellular neural nets; computational fluid dynamics; digital signal processing chips; flow simulation; oceanography; partial differential equations; barotropic ocean model; cell model; cellular neural network universal machine; compressible fluids; emulated digital CNN-UM; incompressible fluids; ocean currents; partial differential equations; Aerodynamics; Computational modeling; Fluid dynamics; Mathematics; Meteorology; Nonlinear equations; Oceans; Partial differential equations; Physics; Power engineering and energy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
  • Conference_Location
    Budapest
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-8359-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2004.1381176
  • Filename
    1381176