• DocumentCode
    2294273
  • Title

    Lightwave neuromorphic signal processing

  • Author

    Prucnal, PAul R. ; Fok, Mable P. ; Rosenbluth, David ; Kravtsov, Konstantin

  • Author_Institution
    Princeton Univ., Princeton, NJ, USA
  • fYear
    2011
  • fDate
    18-20 May 2011
  • Firstpage
    1
  • Lastpage
    2
  • Abstract
    Spike processing devices for optical computational systems have the potential to be scalable, computationally powerful, and have high operation bandwidth. They open up a range of optical processing applications for which electronic processing is too slow. In this paper, we demonstrate the feasibility of implementing simple photonic neuromorphic circuits, including the auditory localization algorithm of the barn owl, which is useful for LIDAR localization, and the crayfish tail-flip escape response. Our approach is based on a hybrid analog/digital computational primitive that elegantly implements the functionality of an integrate-and-fire neuron using a Ge-doped non-linear optical fiber and off-the-shelf semiconductor devices.
  • Keywords
    VLSI; integrated optics; neural nets; nonlinear optics; optical computing; optical fibres; Ge-doped nonlinear optical fiber; LIDAR localization; auditory localization algorithm; barn owl; crayfish tail-flip escape response; electronic processing; hybrid analog/digital computational primitive; integrate-and-fire neuron; lightwave neuromorphic signal processing; off-the-shelf semiconductor devices; optical computational systems; optical processing applications; photonic neuromorphic circuits; spike processing devices; Charge carrier density; Fiber nonlinear optics; Neurons; Optical fibers; Semiconductor optical amplifiers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Photonics (IP), 2011 ICO International Conference on
  • Conference_Location
    Ottawa, ON
  • Print_ISBN
    978-1-61284-315-5
  • Type

    conf

  • DOI
    10.1109/ICO-IP.2011.5953707
  • Filename
    5953707