WHAT CONNECTION TOPOLOGY PROHIBIT CHAOS IN CONTINUOUS TIME NETWORKS?

DOI10.1142/S021952590700129XzbMath1149.92004OpenAlexW2093887716MaRDI QIDQ3521557

Quan Yuan, Xiao-Song Yang, Lin Wang

Publication date: 26 August 2008

Published in: Advances in Complex Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s021952590700129x

zbMATH Keywords

continuous time neural networks

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45) Complex behavior and chaotic systems of ordinary differential equations (34C28)

Cites Work

• An estimation of the domain of attraction and convergence rate for Hopfield continuous feedback neural networks
• Ergodic theory of chaos and strange attractors
• Neurons with graded response have collective computational properties like those of two-state neurons.