Constructing an appropriate membership function integrating fuzzy shannon entropy and human's interval estimation

Takashi Hasuike, Hideki Katagiri, Hiroe Tsubaki

研究成果: Article査読

8 被引用数 (Scopus)

抄録

This paper proposes a new approach of constructing an appropriate membership function to integrate a specific given probability density function, particularly Gaussian function, and fuzzy Shannon entropy extending the information theory based on the human cognitive behavior and subjectivity. The proposed approach is formulated as a more general mathematical programming problem than previous approaches due to using a general Gaussian-based function and the fuzzy Shannon entropy. The optimal condition of parameters is obtained by performing deterministic equivalent transformations to the initial problem. Furthermore, in order to show the appropriate membership function using the proposed approach, some probability density functions are provided as numerical examples.

本文言語English
ページ(範囲)809-813
ページ数5
ジャーナルICIC Express Letters
8
3
出版ステータスPublished - 2014 2月 4
外部発表はい

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンス(全般)

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