Sigmoidal approximations of Heaviside functions in neural lattice models

DOI10.1016/j.jde.2019.11.010zbMath1434.34023OpenAlexW2989143437WikidataQ126777779 ScholiaQ126777779MaRDI QIDQ2297258

Xiaoying Han, Peter E. Kloeden

Publication date: 18 February 2020

Published in: Journal of Differential Equations (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jde.2019.11.010

zbMATH Keywords

global attractorsigmoidal functionHeaviside operatorneural field lattice modelupper semi convergence

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Ordinary differential inclusions (34A60) Discontinuous ordinary differential equations (34A36) Rate of convergence, degree of approximation (41A25) Attractors of solutions to ordinary differential equations (34D45) Ordinary lattice differential equations (34A33)

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