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Type: Artigo de periódico
Title: Storage and recall capabilities of fuzzy morphological associative memories with adjunction-based learning
Author: Valle, ME
Sussner, P
Abstract: We recently employed concepts of mathematical morphology to introduce fuzzy morphological associative memories (FMAMs), a broad class of fuzzy associative memories (FAMs). We observed that many well-known FAM models can be classified as belonging to the class of FMAMs. Moreover, we developed a general learning strategy for FMAMs using the concept of adjunction of mathematical morphology. In this paper, we describe the properties of FMAMs with adjunction-based learning. In particular, we characterize the recall phase of these models. Furthermore, we prove several theorems concerning the storage capacity, noise tolerance, fixed points, and convergence of auto-associative FMAMs. These theorems are corroborated by experimental results concerning the reconstruction of noisy images. Finally, we successfully employ FMAMs with adjunction-based learning in order to implement fuzzy rule-based systems in an application to a time-series prediction problem in industry. (C) 2010 Elsevier Ltd. All rights reserved.
Subject: Fuzzy associative memories
Fuzzy mathematical morphology
Fuzzy learning by adjunction
Storage capacity
Error correction capability
Country: Inglaterra
Editor: Pergamon-elsevier Science Ltd
Citation: Neural Networks. Pergamon-elsevier Science Ltd, v. 24, n. 1, n. 75, n. 90, 2011.
Rights: fechado
Identifier DOI: 10.1016/j.neunet.2010.08.013
Date Issue: 2011
Appears in Collections:Unicamp - Artigos e Outros Documentos

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