NDLI: Fuzzy descriptive models: an interactive framework of information granulation [ECG data]

Content Provider	IEEE Xplore Digital Library
Author	Bortolan, G. Pedrycz, W.
Copyright Year	1993
Abstract	In this paper, we introduce and discuss an important class of endeavors of fuzzy modeling, such as fuzzy descriptive models. In a nutshell, the objective of fuzzy descriptive models is to provide with a sound, comprehensible, and relevant description of experimental data at a general level of relationships revealed there. The elements of such models called descriptors are inherently information granules as the notion of granularity goes hand-in-hand with the interpretability of the resulting constructs (information granules). This paper elaborates on the use of the language of fuzzy sets that are viewed as generic models of information granules. The development of the information granules is carried out in an interactive manner in which a designer can inspect a structure in a data set in a visual fashion. Such visualization is possible through a suitable visualization vehicle provided by self-organizing maps. The role of the designer is to choose from some already visualized regions of the self-organizing map characterized by a high level of data homogeneity. We provide a new algorithm of constructing membership functions of the information granules (fuzzy sets). In addition to some synthetic data, the study includes a comprehensive descriptive modeling of highly dimensional electrocardiogram data.
Sponsorship	IEEE Computational Intelligence Society
Starting Page	743
Ending Page	755
Page Count	13
File Size	2218723
File Format	PDF
ISSN	10636706
Volume Number	10
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-12-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy sets Predictive models Data visualization Self organizing feature maps Numerical models Vehicles Electrocardiography Signal analysis Design methodology Computational intelligence
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Control and Systems Engineering Computational Theory and Mathematics

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