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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 10/2018

22.04.2017 | Original Article

New results on convergence of fuzzy cellular neural networks with multi-proportional delays

verfasst von: Gang Yang

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 10/2018

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Abstract

In this paper, we propose and study the global exponential convergence of a class of fuzzy cellular neural networks with multi-proportional delays, which has not been studied in the existing literature. Applying the differential inequality technique and Lyapunov functional method, we establish a set of global exponential convergence criteria. The sufficient criteria can be easily tested in practice by simple algebra computations. The obtained results play an important role in designing fuzzy neural networks. Moreover, an illustrative example is given to demonstrate our theoretical results.
Vorheriger Artikel Locality similarity and dissimilarity preserving support vector machine
Nächster Artikel Finite-time synchronization by switching state-feedback control for discontinuous Cohen–Grossberg neural networks with mixed delays

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Metadaten
Titel
New results on convergence of fuzzy cellular neural networks with multi-proportional delays
verfasst von
Gang Yang
Publikationsdatum
22.04.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 10/2018
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-017-0672-x

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