POINCARÉ MAPPING OF CONTINUOUS RECURRENT NEURAL NETWORKS EXCITED BY TEMPORAL EXTERNAL INPUT

DOI10.1142/S0218127400001055zbMath1090.34563MaRDI QIDQ5474119

Shozo Sato, Kazutoshi Gohara

Publication date: 23 June 2006

Published in: International Journal of Bifurcation and Chaos (Search for Journal in Brave)

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Qualitative investigation and simulation of ordinary differential equation models (34C60)

Related Items (1)

FRACTAL TRANSITION IN CONTINUOUS RECURRENT NEURAL NETWORKS

Cites Work

• Classification of temporal trajectories by continuous-time recurrent nets
• A learning algorithm to teach spatiotemporal patterns to recurrent neural networks
• DYNAMICAL SYSTEMS EXCITED BY TEMPORAL INPUTS: FRACTAL TRANSITION BETWEEN EXCITED ATTRACTORS
• Neural networks and physical systems with emergent collective computational abilities.
• Neurons with graded response have collective computational properties like those of two-state neurons.

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