NDLI: On the design of an ellipsoid ARTMAP classifier within the fuzzy adaptive system ART framework

Content Provider	IEEE Xplore Digital Library
Author	Peralta, R. Anagnostopoulos, G.C. Gomez-Sanchez, E. Richie, S.
Copyright Year	2005
Description	Author affiliation: Florida Inst. of Technol., Melbourne, FL, USA (Peralta, R.; Anagnostopoulos, G.C.)
Abstract	In this paper we present the design of fuzzy adaptive system ellipsoid ARTMAP (FASEAM), a novel neural architecture based on ellipsoid ARTMAP (EAM) that is equipped with concepts utilized in the fuzzy adaptive system ART (FASART) architecture. More specifically, we derive a new category choice function appropriate for EAM categories that is non-constant in a category's representation region. Additionally, we augment the EAM category description with a centroid vector, whose learning rate is inversely proportional to the number of training patterns accessing the category. Finally, we demonstrate the merits of our design choices by comparing FASART, EAM and FASEAM in terms of generalization performance and final structural complexity on a set of classification problems.
Starting Page	469
Ending Page	474
File Size	1728823
Page Count	6
File Format	PDF
ISBN	0780390482
DOI	10.1109/IJCNN.2005.1555876
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-07-31
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ellipsoids Fuzzy systems Adaptive systems Subspace constraints Fuzzy logic Fuzzy sets Function approximation Resonance Neural networks Prototypes
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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