Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Neural Fuzzy Learning Algorithm Using Neuron Structure

  • Yang, Hwang-Kyu (Department of Computer Engineering , Dongseo University) ;
  • Kim, Kwang-Baek (Major in Computer Engineering, Division of Computer Information Engineering, Silla University) ;
  • Seo, Chang-Jin (Department of Computer Science, Pusan National Universtiy) ;
  • Cha, Eui-Young (Department of Computer Science, Pusan National University)
  • Published : 1998.06.01
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Abstract

In this paper, a method for the improvement of learning speed and convergence rate was proposed applied it to physiological neural structure with the advantages of artificial neural networks and fuzzy theory to physiological neuron structure, To compare the proposed method with conventional the single layer perception algorithm, we applied these algorithms bit parity problem and pattern recognition containing noise. The simulation result indicated that our learning algorithm reduces the possibility of local minima more than the conventional single layer perception does. Furthermore we show that our learning algorithm guarantees the convergence.

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