Efficient decomposition methods of fuzzy relation and their application to image decomposition

Hajime Nobuhara; Kaoru Hirota; Salvatore Sessa; Witold Pedrycz

doi:10.1016/j.asoc.2004.09.002

Efficient decomposition methods of fuzzy relation and their application to image decomposition

Hajime Nobuhara^*
, Kaoru Hirota
, Salvatore Sessa
, Witold Pedrycz

^*此作品的通讯作者

Tokyo Institute of Technology
University of Naples Federico II
University of Alberta

科研成果: 期刊稿件 › 文章 › 同行评审

20 引用（Scopus）

摘要

Two optimizations for decomposition problem of fuzzy relation (image) are proposed. The first optimization is a fast decomposition method of fuzzy relation based on the properties of max and min operations and the simultaneous updating of the prototype. The second optimization corresponds to an improvement of a cost function, in order to obtain a good quality of the solution of the decomposition problem.

源语言	英语
页（从-至）	399-408
页数	10
期刊	Applied Soft Computing
卷	5
期	4
DOI	https://doi.org/10.1016/j.asoc.2004.09.002
出版状态	已出版 - 7月 2005
已对外发布	是

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10.1016/j.asoc.2004.09.002

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title = "Efficient decomposition methods of fuzzy relation and their application to image decomposition",

abstract = "Two optimizations for decomposition problem of fuzzy relation (image) are proposed. The first optimization is a fast decomposition method of fuzzy relation based on the properties of max and min operations and the simultaneous updating of the prototype. The second optimization corresponds to an improvement of a cost function, in order to obtain a good quality of the solution of the decomposition problem.",

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author = "Hajime Nobuhara and Kaoru Hirota and Salvatore Sessa and Witold Pedrycz",

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T1 - Efficient decomposition methods of fuzzy relation and their application to image decomposition

AU - Nobuhara, Hajime

AU - Hirota, Kaoru

AU - Sessa, Salvatore

AU - Pedrycz, Witold

PY - 2005/7

Y1 - 2005/7

N2 - Two optimizations for decomposition problem of fuzzy relation (image) are proposed. The first optimization is a fast decomposition method of fuzzy relation based on the properties of max and min operations and the simultaneous updating of the prototype. The second optimization corresponds to an improvement of a cost function, in order to obtain a good quality of the solution of the decomposition problem.

AB - Two optimizations for decomposition problem of fuzzy relation (image) are proposed. The first optimization is a fast decomposition method of fuzzy relation based on the properties of max and min operations and the simultaneous updating of the prototype. The second optimization corresponds to an improvement of a cost function, in order to obtain a good quality of the solution of the decomposition problem.

KW - Fuzzy relation

KW - Gradient method

KW - Image decomposition

KW - Optimization

UR - https://www.scopus.com/pages/publications/18844425991

U2 - 10.1016/j.asoc.2004.09.002

DO - 10.1016/j.asoc.2004.09.002

M3 - Article

AN - SCOPUS:18844425991

SN - 1568-4946

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SP - 399

EP - 408

JO - Applied Soft Computing

JF - Applied Soft Computing

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Efficient decomposition methods of fuzzy relation and their application to image decomposition

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