Anti-periodic solutions for Clifford-valued high-order Hopfield neural networks with state-dependent and leakage delays

• Autorzy: Huo Nina , Li Bing , Li Yongkun

Identyfikatory

DOI

10.34768/amcs-2020-0007

• Języki publikacji: EN

Abstrakty

EN

A class of Clifford-valued high-order Hopfield neural networks (HHNNs) with state-dependent and leakage delays is considered. First, by using a continuation theorem of coincidence degree theory and the Wirtinger inequality, we obtain the existence of anti-periodic solutions of the networks considered. Then, by using the proof by contradiction, we obtain the global exponential stability of the anti-periodic solutions. Finally, two numerical examples are given to illustrate the feasibility of our results.

Słowa kluczowe

EN

Hopfield neural network; anti-periodic solution; coincidence degree; time-varying delay

PL

sieć neuronowa Hopfielda; stopień koincydencji; opóźnienie czasowo zależne

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2020
• Tom: Vol. 30, no. 1
• Strony: 83--98
• Opis fizyczny: Bibliogr. 42 poz., rys.

Twórcy

autor

Huo Nina

• Department of Mathematics, Yunnan University, Kunming, Yunnan 650091, People’s Republic of China

autor

Li Bing

• School of Mathematics and Computer Science, Yunnan Nationalities University, Kunming, Yunnan 650500, People’s Republic of China

autor

Li Yongkun

• Department of Mathematics, Yunnan University, Kunming, Yunnan 650091, People’s Republic of China

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).