Input-Anticipating Critical Reservoirs Show Power Law Forgetting of Unexpected Input Events

DOI10.1162/NECO_a_00730zbMath1475.92017arXiv1404.6334OpenAlexW2028324893WikidataQ50596067 ScholiaQ50596067MaRDI QIDQ5380243

N. Michael Mayer

Publication date: 4 June 2019

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1404.6334

zbMATH Keywords

chaotic dynamicslayersynaptic weightEcho state

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Memory and learning in psychology (91E40)

Cites Work

• Unnamed Item
• Unnamed Item
• Re-visiting the echo state property
• Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons
• Criticality in Neural Systems

This page was built for publication: Input-Anticipating Critical Reservoirs Show Power Law Forgetting of Unexpected Input Events