• DocumentCode
    2286379
  • Title

    Basic mammalian retinal effects on the prototype complex cell CNN universal machine

  • Author

    Balya, D. ; Rekeczky, Cs ; Roska, T.

  • Author_Institution
    Analogical & Neural Comput. Lab., Comput. & Autom. Res. Inst., Budapest, Hungary
  • fYear
    2002
  • fDate
    22-24 Jul 2002
  • Firstpage
    251
  • Abstract
    The unique possibility for reconstructing the first stage of the visual system on a programmable silicon chip is described. The developed mammalian retinal model can be implemented as an analogic algorithm running on a prototype complex cell cellular neural network processor. It enables the neuro-biological and vision research communities to study the wisdom of biological visual transformations design in real-time. The operating prototype complex-cell CNN-UM processor opens a new world for the engineering as well as the computational neuroscience communities. This paper demonstrates the first steps in this direction. Here we present the decomposition and scaling of one retinal channel as a hardware-level CNN-UM algorithm. The analogic algorithm consists of a series of different complex-cell CNN spatial-temporal dynamics, feasible on the recently fabricated prototype complex cell CNN-UM chip.
  • Keywords
    biology computing; cellular neural nets; neurophysiology; physiological models; vision; CNN-UM processor; cellular neural network processor; cellular nonlinear network universal machine; computational neuroscience; decomposition; mammalian retina; scaling; spatial-temporal dynamics; visual system; Biological system modeling; Biology computing; Cellular neural networks; Design engineering; Neuroscience; Prototypes; Retina; Silicon; Turing machines; Visual system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and Their Applications, 2002. (CNNA 2002). Proceedings of the 2002 7th IEEE International Workshop on
  • Print_ISBN
    981-238-121-X
  • Type

    conf

  • DOI
    10.1109/CNNA.2002.1035058
  • Filename
    1035058