• DocumentCode
    3223099
  • Title

    Dialog concepts for learning retina encoders

  • Author

    Eckmiller, R. ; Becker, M. ; Hunermann, R.

  • Author_Institution
    Dept. of Comput. Sci. VI, Bonn Univ., Germany
  • Volume
    4
  • fYear
    1997
  • fDate
    9-12 Jun 1997
  • Firstpage
    2315
  • Abstract
    This paper defines the biomedical and technological constraints for retina implants and describes our recent results and concepts regarding the function and training of learning retina encoder (RE) by means of neural networks. We show that: 1) system identification of a portable Mark I RE in analog hardware with tunable RF-filters can be achieved by means of supervised learning in connection with a neural net; and 2) the tunable RE-filters of a Mark II RE as DSP implementation can be tuned individually to typical RF properties of primate retinal ganglion cells in real time. These results demonstrate the feasibility of approximating the retinal information processing by means of tunable RF-filters in a RE system with a photosensor array at the input and simulated ganglion cells at the output. A concept is presented for training the learning RE with tunable RE-filters in a dialog with human subjects using their visual perception
  • Keywords
    encoding; eye; identification; neural nets; orthotics; photodetectors; radiofrequency filters; vision defects; visual evoked potentials; visual perception; ganglion cells; neural networks; photosensor array; retina encoders; retina implants; retinal information processing; supervised learning; system identification; tunable RF-filters; visual perception; Digital signal processing; Hardware; Implants; Information processing; Neural networks; Radio frequency; Real time systems; Retina; Supervised learning; System identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks,1997., International Conference on
  • Conference_Location
    Houston, TX
  • Print_ISBN
    0-7803-4122-8
  • Type

    conf

  • DOI
    10.1109/ICNN.1997.614420
  • Filename
    614420