Stochastic approach for assessing the predictability of chaotic time series using reservoir computing

DOI10.1063/5.0058439zbMATH Open1546.37154MaRDI QIDQ6556907

I. A. Khovanov

Publication date: 17 June 2024

Published in: Chaos (Search for Journal in Brave)

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Numerical chaos (65P20) Approximation methods and numerical treatment of dynamical systems (37M99)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• On models with non-rough Poincaré homoclinic curves
• Runge-Kutta Methods with Minimum Error Bounds
• On dynamical properties of multidimensional diffeomorphisms from Newhouse regions: I
• Deterministic Nonperiodic Flow
• GIBBS MEASURES IN ERGODIC THEORY
• Numerical Methods for Ordinary Differential Equations
• Beitrag zur näherungsweisen Integration totaler Differentialgleichungen.

Related Items (1)

Introduction to focus issue: in memory of Vadim S. Anishchenko: statistical physics and nonlinear dynamics of complex systems

This page was built for publication: Stochastic approach for assessing the predictability of chaotic time series using reservoir computing