Potsdam Institute for Climate Impact Research (PIK)
Interdisciplinary Center for Dynamics of Complex Systems (University of Potsdam)
Cardiovascular Physics Group (Humboldt-Universität zu Berlin)
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TOCSY - Toolboxes for Complex Systems
PIK/ Antique/ Blue
Home Home
Innovative filtering of Data Filtering
Time-scale adjustment Time-Scale Adjustment
Nonlinear correlation/ interrelation analysis Nonlinear Correlation
Parameter estimation of models System Identification
Data analysis and modeling using complex networks. Complex Networks
Investigation of system\'s dynamics System's Dynamics

System Identification

Tools

System
Identification Tool

Example: Two-dimensional reaction-diffusion system

The system identification tool is applied to a two-dimensional reaction-diffusion system in order to filter the data and to estimate model parameters. This system has a rich spatiotemporal dynamical behavior. If excited, the underlying chemical system produces concentration differences propagating through the chemical reactor. Target and spiral patterns are observed as well as spiral defect chaos. The underlying complex chemical reaction is simplified to a system of two variables, an activator v1 and an inhibitor v2.

Observation and filtering.

Noisy observation (left) and the estimated pattern v1 and v2.

Estimated parameter.

Estimated parameter for a model describing the reaction-diffusion system for different initial guesses. The true parameter is λ=1.

Reference:

Sitz, A., Kurths, J., Voss, H. U.: Identification of nonlinear spatiotemporal systems via partitioned filtering, Phys. Rev. E, 68, 2003, 016202, doi:10.1103/PhysRevE.68.016202, Article (PDF).


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University of Potsdam, Interdisciplinary Center for Dynamics of Complex Systems, Germany
Potsdam Institute for Climate Impact Research, Complexity Science, Germany

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