• DocumentCode
    1646113
  • Title

    Dynamical digital silicon neurons

  • Author

    Cassidy, Andrew ; Andreou, Andreas G.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD
  • fYear
    2008
  • Firstpage
    289
  • Lastpage
    292
  • Abstract
    We present an array of dynamical digital silicon neurons implementing the Izhikevich neuron model. The FPGA based array consists of 32 physical neurons, each time multiplexing the state of 8 virtual neurons, for a total of 256 independent neurons. The neural array operates at 5,000 times faster than real time, performing over 20.48 GOPS (giga operations per second). It is intended for neural simulation acceleration, neural prostheses, and neuromorphic systems.
  • Keywords
    field programmable gate arrays; neurophysiology; physiological models; silicon; FPGA; Izhikevich neuron model; Si; dynamical digital silicon neurons; multiplexing; neural prostheses; neural simulation acceleration; neuromorphic systems; Acceleration; Biological system modeling; Biology computing; Computational modeling; Computer architecture; Field programmable gate arrays; Neuromorphics; Neurons; Prosthetics; Silicon;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Circuits and Systems Conference, 2008. BioCAS 2008. IEEE
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    978-1-4244-2878-6
  • Electronic_ISBN
    978-1-4244-2879-3
  • Type

    conf

  • DOI
    10.1109/BIOCAS.2008.4696931
  • Filename
    4696931
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1646113