Transistor-based chaotic oscillators are known to realize highly diverse dynamics despite having elementary cir-cuit topologies. This work investigates, numerically and experimentally using a ring network, a recently -intro-duced dual-transistor circuit that generates neural-like spike trains. A multitude of non-trivial effects are observed as a function of the supply voltage and coupling strength, including pattern formation under incom-plete synchronization and sensitivity to additional long-distance links. Globally-applied noise exerts a synchro-nizing effect that interacts with the other control parameters. When the network is partitioned in halves at different levels of granularity, their interplay gives rise to adversarial route-to-synchronization phenomena. These results highlight the generative ability of this circuit and motivate its consideration towards the future realization of physical reservoirs.(c) 2022 Elsevier Ltd. All rights reserved.

Synchronization phenomena in dual-transistor spiking oscillators realized experimentally towards physical reservoirs

Frasca M.;
2022-01-01

Abstract

Transistor-based chaotic oscillators are known to realize highly diverse dynamics despite having elementary cir-cuit topologies. This work investigates, numerically and experimentally using a ring network, a recently -intro-duced dual-transistor circuit that generates neural-like spike trains. A multitude of non-trivial effects are observed as a function of the supply voltage and coupling strength, including pattern formation under incom-plete synchronization and sensitivity to additional long-distance links. Globally-applied noise exerts a synchro-nizing effect that interacts with the other control parameters. When the network is partitioned in halves at different levels of granularity, their interplay gives rise to adversarial route-to-synchronization phenomena. These results highlight the generative ability of this circuit and motivate its consideration towards the future realization of physical reservoirs.(c) 2022 Elsevier Ltd. All rights reserved.
2022
Chaos generation
Pattern formation
Reservoir computing
Spiking dynamics
Transistor
 
Synchronization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/555583
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