Neural networks and chaos: Construction, evaluation of chaotic networks, and prediction of chaos with multilayer feedforward networks

DOI10.1063/1.3685524zbMath1331.92013arXiv1608.05916OpenAlexW2964065171WikidataQ45891795 ScholiaQ45891795MaRDI QIDQ2787720

Jean-François Couchot, Michel Salomon, Christophe Guyeux, Jacques M. Bahi

Publication date: 4 March 2016

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

Full work available at URL: https://arxiv.org/abs/1608.05916

zbMATH Keywords

Boolean functionschaotic behaviormultilayer feedforward networks

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45)

Related Items (1)

Domain-Structured Chaos in a Hopfield Neural Network

Cites Work

• Unnamed Item
• Multilayer feedforward networks are universal approximators
• An image encryption approach based on chaotic maps
• Hash Functions Using Chaotic Iterations
• Approximation by superpositions of a sigmoidal function

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