Fuzzy-neunet: A non standard neural network

  • Paul Andlinger
  • Ernst R. Reichl
Neural Network Architectures And Algorithms
Part of the Lecture Notes in Computer Science book series (LNCS, volume 540)


Most of today's connectionist networks hold the information in the weights of the connections, the synapses (see Error Back Propagation, Hopfield-Net, Neocognitron). In contrast to these models NEUNET is a fully self organizing network. Its information is represented only in its overall structure, which is adopted dynamically through new ‘experiences’ and a special type of persistent activation-states (the so-called stamps) of the units.

The goal of this paper is to give an overview of the NEUNET-algorithms as well as of its theoretical background. The main part is dedicated to a new probability-based approach which does significantly improve the capabilities of NEUNET. Some characteristic examples are given for illustrating applications in pattern recognition with autoassociative recall. In addition to a presentation of the current state of development of NEUNET a description of prospects of future work is given.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Paul Andlinger
    • 1
  • Ernst R. Reichl
    • 1
  1. 1.Institut für InformatikJohannes Kepler UniversityLinzAustria

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