Efficient noncausal noise reduction for deterministic time series

DOI10.1063/1.1357454zbMath1080.37598OpenAlexW2056428637WikidataQ52015691 ScholiaQ52015691MaRDI QIDQ5706257

Ulrich Parlitz, Joach Bröcker

Publication date: 7 November 2005

Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1063/1.1357454

Mathematics Subject Classification ID

Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45) Time series analysis of dynamical systems (37M10)

Related Items

Shadowing-Based Data Assimilation Method for Partially Observed Models, Projected Shadowing-Based Data Assimilation, Optimal projection filters with information geometry, Error covariance matrix estimation of noisy and dynamically coupled time series, Geometric noise reduction for multivariate time series, Topology-based signal separation, NONLINEAR DYNAMICAL SYSTEM IDENTIFICATION FROM UNCERTAIN AND INDIRECT MEASUREMENTS, Noise reduction by recycling dynamically coupled time series

Cites Work

• Optimal shadowing and noise reduction
• A noise reduction method for signals from nonlinear systems
• Noise reduction in chaotic time series using scaled probabilistic methods
• NOISE REDUCTION BY GRADIENT DESCENT
• On noise reduction methods for chaotic data