https://doi.org/10.1140/epjs/s11734-021-00162-5
Regular Article
Emulating complex networks with a single delay differential equation
1
Institute of Mathematics, Technische Universität Berlin, Berlin, Germany
2
Department of Mathematics, Humboldt-Universität zu Berlin, Berlin, Germany
Received:
27
November
2020
Accepted:
23
April
2021
Published online:
6
June
2021
A single dynamical system with time-delayed feedback can emulate networks. This property of delay systems made them extremely useful tools for Machine-Learning applications. Here, we describe several possible setups, which allow emulating multilayer (deep) feed-forward networks as well as recurrent networks of coupled discrete maps with arbitrary adjacency matrix by a single system with delayed feedback. While the network’s size can be arbitrary, the generating delay system can have a low number of variables, including a scalar case.
© The Author(s) 2021
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