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

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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Nobuhara, H., Hirota, K., Sessa, S., & Pedrycz, W. (2005). Efficient decomposition methods of fuzzy relation and their application to image decomposition. Applied Soft Computing, 5(4), 399-408. https://doi.org/10.1016/j.asoc.2004.09.002

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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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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

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

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