The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Fuzzy Combined Polynomial Neural Networks

퍼지 결합 다항식 뉴럴 네트워크

  • 노석범 (원광대학 제어계측 공학과) ;
  • 오성권 (수원대학 전기공학과) ;
  • 안태천 (원광대학 전기전자 및 정보 공학부)
  • Published : 2007.07.01
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Abstract

In this paper, we introduce a new fuzzy model called fuzzy combined polynomial neural networks, which are based on the representative fuzzy model named polynomial fuzzy model. In the design procedure of the proposed fuzzy model, the coefficients on consequent parts are estimated by using not general least square estimation algorithm that is a sort of global learning algorithm but weighted least square estimation algorithm, a sort of local learning algorithm. We are able to adopt various type of structures as the consequent part of fuzzy model when using a local learning algorithm. Among various structures, we select Polynomial Neural Networks which have nonlinear characteristic and the final result of which is a complex mathematical polynomial. The approximation ability of the proposed model can be improved using Polynomial Neural Networks as the consequent part.

Keywords

References

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