Literature DB >> 26655372

Boundedness, Mittag-Leffler stability and asymptotical ω-periodicity of fractional-order fuzzy neural networks.

Ailong Wu1, Zhigang Zeng2.   

Abstract

We show that the ω-periodic fractional-order fuzzy neural networks cannot generate non-constant ω-periodic signals. In addition, several sufficient conditions are obtained to ascertain the boundedness and global Mittag-Leffler stability of fractional-order fuzzy neural networks. Furthermore, S-asymptotical ω-periodicity and global asymptotical ω-periodicity of fractional-order fuzzy neural networks is also characterized. The obtained criteria improve and extend the existing related results. To illustrate and compare the theoretical criteria, some numerical examples with simulation results are discussed in detail. Crown
Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Keywords:  -asymptotical -periodicity; Boundedness; Fractional-order systems; Fuzzy neural networks; Mittag-Leffler stability

Mesh:

Year:  2015        PMID: 26655372     DOI: 10.1016/j.neunet.2015.11.003

Source DB:  PubMed          Journal:  Neural Netw        ISSN: 0893-6080


  2 in total

1.  Global [Formula: see text] stabilization of fractional-order memristive neural networks with time delays.

Authors:  Ling Liu; Ailong Wu; Xingguo Song
Journal:  Springerplus       Date:  2016-07-09

2.  Artificial neural networks: a practical review of applications involving fractional calculus.

Authors:  E Viera-Martin; J F Gómez-Aguilar; J E Solís-Pérez; J A Hernández-Pérez; R F Escobar-Jiménez
Journal:  Eur Phys J Spec Top       Date:  2022-02-12       Impact factor: 2.891

  2 in total

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