Reservoir computing with random and optimized time-shifts

DOI10.1063/5.0068941zbMATH Open1545.68046MaRDI QIDQ6558708

Afroza Shirin, Enrico Del Frate, Francesco Sorrentino

Publication date: 21 June 2024

Published in: Chaos (Search for Journal in Brave)

Mathematics Subject Classification ID

Could not fetch data.

Cites Work

• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• Simple recurrent networks learn context-free and context-sensitive languages by counting.
• Dynamic mode decomposition of numerical and experimental data
• Do reservoir computers work best at the edge of chaos?
• Fading memory and the problem of approximating nonlinear operators with Volterra series
• Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
• Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data
• Stability analysis of reservoir computers dynamics via Lyapunov functions
• On explaining the surprising success of reservoir computing forecaster of chaos? The universal machine learning dynamical system with contrast to VAR and DMD
• Path length statistics in reservoir computers
• Dimension of reservoir computers

Related Items (2)

Erratum to: ``Reservoir computing with random and optimized time-shifts ⋮ Time shifts to reduce the size of reservoir computers

This page was built for publication: Reservoir computing with random and optimized time-shifts

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6558708)