• DocumentCode
    3273700
  • Title

    An artificial neural network accelerator for pulse coded model-neurons

  • Author

    Frank, G. ; Hartmann, G.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Paderborn Univ., Germany
  • Volume
    4
  • fYear
    1995
  • fDate
    Nov/Dec 1995
  • Firstpage
    2014
  • Abstract
    The following report introduces the hardware design of a neuro-computer aligned to simulate large neural nets consisting of pulse-coded model neurons. The simulation process is carried out in real-time, referring to image processing. A single accelerator provides 32k neurons with 128 synapses each. There is no need to assign a fixed number of synaptic weights to each neuron rather then distributing the total amount of four million synapses arbitrary to any neuron. The simulation of larger nets is possible by connecting the accelerators in a hexagonal structure, where the simulation time will only increase if the overall activity of the net mainly effects one specific accelerator board
  • Keywords
    computer vision; image processing; neural nets; object recognition; real-time systems; computer vision; image processing; neural network accelerator; neuro-computer; object recognition; pulse coded model-neurons; real-time system; simulation process; synaptic weights; Artificial neural networks; Biological system modeling; Computational modeling; Electron accelerators; Hardware; Humans; Joining processes; Neurons; Object recognition; Visual system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1995. Proceedings., IEEE International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-2768-3
  • Type

    conf

  • DOI
    10.1109/ICNN.1995.488982
  • Filename
    488982