Convergence of asymptotic systems of non-autonomous neural network models with infinite distributed delays

DOI10.1007/s00332-017-9371-8zbMath1382.34093OpenAlexW2591430550MaRDI QIDQ1682994

José J. Oliveira

Publication date: 6 December 2017

Published in: Journal of Nonlinear Science (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1822/46289

zbMATH Keywords

global convergenceneural networksinfinite distributed delaysasymptotic systems

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Asymptotic theory of functional-differential equations (34K25) Growth, boundedness, comparison of solutions to functional-differential equations (34K12) Qualitative investigation and simulation of models involving functional-differential equations (34K60)

Related Items (1)

Robust delay-dependent stability of uncertain inertial neural networks with impulsive effects and distributed-delay

Uses Software

• Matlab
• dde23

Cites Work

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• Global Attractivity in Delayed Hopfield Neural Network Models
• Neurons with graded response have collective computational properties like those of two-state neurons.
• Solving DDEs in Matlab

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