2006/01/30 by Christopher C. Strelioff, Alfred Hübler · 3 citations
Computer Science · Economics, Econometrics and Finance · Physics and Astronomy · #Chaos control and synchronization #Complex Systems and Time Series Analysis #Nonlinear Dynamics and Pattern Formation
paper · doi:10.1103/physrevlett.96.044101
openalex publication_date 2006/01/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/26
We study prediction of chaotic time series when a perfect model is available but the initial condition is measured with uncertainty. A common approach for predicting future data given these circumstances is to apply the model despite the uncertainty. In systems with fold dynamics, we find prediction is improved over this strategy by recognizing this behavior. A systematic study of the Logistic map demonstrates prediction of the most likely trajectory can be extended three time steps. Finally, we discuss application of these ideas to the Rössler attractor.