• DocumentCode
    465047
  • Title

    Models of Lava Flow Through the CNN-Based E^3 Architecture

  • Author

    Arena, P. ; Buscemi, G. ; Carambia, B. ; Del Negro, C. ; Fortuna, L. ; Frasca, M. ; Vicari, A.

  • Author_Institution
    Dipt. di Ingegneria Elettrica, Elettronica e dei Sistemi, Universita degli Studi di Catania
  • fYear
    2007
  • fDate
    27-30 May 2007
  • Firstpage
    2914
  • Lastpage
    2917
  • Abstract
    Many works investigated the phenomenon of lava flow through numerical models, obtaining excellent results, although most of the models require several approximations. Each model, in fact, has its restrictions: for instance, some of them work only on inclined planes, while others do not consider cooling processes associated to lava flow and so on. Simplifications are often needed to afford the computational effort required by the problem. Although the increasing computational capability of computers, due to technological progress, can be very useful to quickly resolve differential equations, which are essential to study lava flows, it is still important to take into account alternative solutions to the problem. One of these solutions is the use of parallel analog processors, namely cellular nonlinear networks (CNNs). In particular, the approach used in this work is based on the E^3 architecture (Caponetto et al., 2004) used for the first time to study lava flows. Two different models are proposed.
  • Keywords
    cellular neural nets; differential equations; geophysics computing; CNN-based E^3 architecture; cellular nonlinear networks; cooling process; differential equations; lava flow; numerical models; parallel analog processors; Cellular neural networks; Computational modeling; Computer architecture; Cooling; Differential equations; Emergent phenomena; Numerical models; Parallel algorithms; Parallel processing; Surfaces;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2007. ISCAS 2007. IEEE International Symposium on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    1-4244-0920-9
  • Electronic_ISBN
    1-4244-0921-7
  • Type

    conf

  • DOI
    10.1109/ISCAS.2007.377859
  • Filename
    4253288