An Analog VLSI Pulsed Neural Network for Image Segmentation Using Adaptive Connection Weights

  • Authors:

  • Arne Heittmann;Ulrich Ramacher;Daniel Matolin;Jörg Schreiter;René Schüffny

  • Affiliations:

  • -;-;-;-;-

  • Venue:
  • ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
  • Year:
  • 2002

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Abstract

An analog VLSI pulsed neural network for image segmentation using adaptive connection weights is presented. The network marks segments in the image through synchronous firing patterns. The synchronization is achieved through adaption of connection weights. The adaption uses only local signals in a data-driven and self-organizing way. It is shown that for the proposed adaption rules a simple analog VLSI implementation is feasible due to the required local connections and the data-driven self-organizing approach.