A generalized neural network architecture based on distributed signal processing

  • Authors:

  • Askin Demirkol

  • Affiliations:

  • Department of Electrical and Computer Engineering, University of Missouri-Rolla, MO

  • Venue:
  • RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
  • Year:
  • 2006

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Abstract

In this paper, an unstructured neural network based on the mathematics of holographic storage is presented. While the holographic process is analyzed by the distributed signal processing principles, the neural network architecture is adapted to the generalized support vector machine. This work is inspired by similarities between brain waves and the wave propagation and subsequent interference patterns seen in holograms. Then the mathematics to produce a general mathematical description of the holographic process is analyzed. From this analysis it is shown that how the holographic process can be used as an associative memory network. This aspect, makes this neural network formation process particularly useful for control