Anti-periodic solution for fuzzy Cohen–Grossberg neural networks with time-varying and distributed delays

In this paper, by using a continuation theorem of coincidence degree theory and a differential inequality, we establish some sufficient conditions ensuring the existence and global exponential stability of anti-periodic solutions for a class of fuzzy Cohen–Grossberg neural networks with time-varying...

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Veröffentlicht in:Nonlinear analysis (Vilnius, Lithuania) Lithuania), 2015-07, Vol.20 (3), p.395-416
Hauptverfasser: Li, Yongkun, Yang, Li, Wu, Wanqin
Format: Artikel
Sprache:eng
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Zusammenfassung:In this paper, by using a continuation theorem of coincidence degree theory and a differential inequality, we establish some sufficient conditions ensuring the existence and global exponential stability of anti-periodic solutions for a class of fuzzy Cohen–Grossberg neural networks with time-varying and distributed delays. In addition, we present an illustrative example to show the feasibility of obtained results.
ISSN:1392-5113
2335-8963
DOI:10.15388/NA.2015.3.6