Fuzzy data granulation and relational compression

Kaoru Hirota*, Witold Pedrycz

*此作品的通讯作者

科研成果: 期刊稿件会议文章同行评审

摘要

This study concentrates on fuzzy relational calculus and views it as a basis of data granulation and data compression. In this setting, data and images, in particular, are represented as fuzzy relations. We investigate fuzzy relational equations as a vehicle of data compression. It is shown that both compression and decompression (reconstruction) phases are closely linked with the way in which fuzzy relational equations are being usually formulated and solved. The underlying findings that are encountered in the theory of these equations are easily accommodated as an important backbone of any relational compression. The character of the solutions to the equations make them ideal for reconstruction purposes as they specify the extremal elements of the solution set and in such a way help establish some envelopes of the original images under compression. The flexibility of the conceptual and algorithmic framework arising there is also discussed. Numerical examples provide a suitable illustrative material emphasizing the main features of the compression mechanisms.

源语言英语
页(从-至)V-900 - V-905
期刊Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
5
出版状态已出版 - 1999
已对外发布
活动1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn
期限: 12 10月 199915 10月 1999

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