Stability on Positive Almost Periodic High-Order Hopfield Neural Networks

한국수학교육학회지시리즈B:순수및응용수학 / Journal of the Korean Society of Mathematical Education Series B: The Pure and Applied Mathematics, (P)1226-0657; (E)2287-6081

2024, v.31 no.4, pp.415-425

https://doi.org/10.7468/jksmeb.2024.31.4.415

Feng Liu (Changsha University of Science and Technolog)

Feng, L. (2024). . 한국수학교육학회지시리즈B:순수및응용수학, 31(4), 415-425, https://doi.org/10.7468/jksmeb.2024.31.4.415

복사

Abstract

This essay explores a class of almost periodic high-order Hopfield neural networks involving time-varying delays. By taking advantage of some novel differential inequality techniques, several assertions are derived to substantiate the positive exponential stability of the addressed neural networks, which refines and extends the corresponding results in some existing references. In particular, a demonstrative experiment is presented to check the effectiveness and validity of the theoretical outcomes.

keywords: high-order Hopfield neural networks, almost periodic solution, exponential stability, time-varying delay

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논문 상세

Vol.31 No.4

Stability on Positive Almost Periodic High-Order Hopfield Neural Networks

Abstract

한국수학교육학회지시리즈B:순수및응용수학