Optimizing algebraic and neural methods for information processing in distributed fiber-optical measuring systems

  • Authors:

  • Yu. N. Kulchin;E. V. Zakasovskaya

  • Affiliations:

  • Institute for Automation and Control Processes FEB RAS, Vladivostok, Russia 690041;Far-Eastern State University, Vladivostok, Russia 690000

  • Venue:
  • Optical Memory and Neural Networks
  • Year:
  • 2010

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Abstract

The paper discusses tomography reconstruction of distributed physical fields by means of fiber optical measuring systems (FOMN) [1] for parallel setup of measuring lines with a small number of scanning directions. The approach whose novelty involves measuring network geometry optimization for further application of neural or algebraic technologies to restore a full image of the functions studied is presented. An alternative to choose and apply an appropriate neural network from the set of several, previously trained neural networks of radial-basic type is investigated [2].