대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)

대한전기학회 (The Korean Institute of Electrical Engineers)
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경쟁적 퍼지 다항식 뉴론을 가진 자기 구성 네트워크의 설계

Design of Self-Organizing Networks with Competitive Fuzzy Polynomial Neuron

  • 박호성 (원광대학교 전기전자공학부) ;
  • 오성권 (원광대학교 전기전자공학부) ;
  • 김현기 (수원대학교 전기전자정보통신공학부)
  • Park, Ho-Sung (School of Electrical & Electronic Engineering, Wonkwang Univ.) ;
  • Oh, Sung-Kwun (School of Electrical & Electronic Engineering, Wonkwang Univ.) ;
  • Kim, Hyun-Ki (Dept. of Electrical Engineering, Suwon Univ.)
  • 발행 : 2000.11.25
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초록

In this paper, we propose the Self-Organizing Networks(SON) based on competitive Fuzzy Polynomial Neuron(FPN) for the optimal design of nonlinear process system. The SON architectures consist of layers with activation nodes based on fuzzy inference rules. Here each activation node is presented as FPN which includes either the simplified or regression Polynomial fuzzy inference rules. The proposed SON is a network resulting from the fusion of the Polynomial Neural Networks(PNN) and a fuzzy inference system. The conclusion part of the rules, especially the regression polynomial uses several types of high-order polynomials such as liner, quadratic and modified quadratic. As the premise part of the rules, both triangular and Gaussian-like membership functions are studied. Chaotic time series data used to evaluate the performance of our proposed model.

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