• DocumentCode
    2560416
  • Title

    Simulation-framework for purely digital CNN/MRF-architectures

  • Author

    Stilkerich, Stephan C.

  • Author_Institution
    Image & Signal Process. Group, EADS Corporate Res. Center, Munich, Germany
  • fYear
    2005
  • fDate
    28-30 May 2005
  • Firstpage
    94
  • Lastpage
    97
  • Abstract
    Any kind of hardware-relevant modeling, simulation and analysis of purely digital and massively parallel architectures, which is based on CNN/MRF processing principles is a time consuming, computing resources intensive, fault-prone and complex task. Until now there is no industrially qualified toolkit available to systematically support these tasks in a single closed environment. In this paper we present a novel simulation-framework for purely digital CNN/MRF processing systems. The unique modeling, hardware-relevant simulation and analysis capabilities unified in this simulation-framework allows it to systematically investigate (1) the massively parallel processing dynamic of digital CNN/MRF devices, (2) the model´s convergence behavior and (3) complete CNN/MRF systems with an application-specific size. The paper is finalized by simulation results demonstrating the ability of the framework to handle CNN/MRF processing systems of realistic size and complexity. This manifests the industrial relevance of the proposed CNN/MRF simulation-framework.
  • Keywords
    Markov processes; cellular neural nets; neural net architecture; parallel processing; random processes; Markov random field; massively parallel processing; purely digital CNN/MRF-architectures; simulation framework; Analytical models; Application specific integrated circuits; Cellular neural networks; Computational modeling; Environmental management; Infrared sensors; Mathematical model; Radiation hardening; Signal processing; Space technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and Their Applications, 2005 9th International Workshop on
  • Print_ISBN
    0-7803-9185-3
  • Type

    conf

  • DOI
    10.1109/CNNA.2005.1543169
  • Filename
    1543169