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DSWeb Dynamical Systems Software aims to collect all available software on dynamical systems theory. This project was originally launched during the special year Emerging Applications of Dynamical Systems, 1997/1998, at the Institute for Mathematics and its Applications. The information here includes functionality, platforms, languages, references, and contacts.

Please note that DSWeb is not responsible for any direct, indirect, special, incidental, or consequential damages arising from the use of the content provided here.

TOCSY

By Norbert Marwan
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TOCSY

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The toolbox is a collection of packages for data pre-processing, data analysis and model fitting for using with Matlab®.

For data pre-processing, an adaptive filter, an unscented Kalman filter and a tool for the adjustment of time scales by using recurrence plots are available. The components for the data analysis allow to investigate the systems dynamics, correlations/ interrelations as well as phase coherency. It includes, e.g., optimal transformations and maximal correlations based on ACE, comprehensive recurrence analysis (recurrence plot based methods) or cross wavelet analysis. A system identification toolbox based on an unscented Kalman filter can be used in order to estimate model parameters. If the physiological model is known, the parameters can be estimated which can be used in order to produce the observed data.

KeywordsIdentification, Time series analysis, Visualization
Model
  • Maps
  • ODEs
  • Time Series
  • Other
Software Type
  • Package
Language
  • MatLab
Platform
  • Unix
  • Linux
  • Windows
  • MacOS
  • Other
Availability
Contact Person
Dr. Norbert Marwan
Nonlinear Dynamics Group
University of Potsdam
E-mail: [email protected]
References to Papers
  1. H. Voss and J. Kurths. Reconstruction of nonlinear time delay models from data by the use of optimal transformations, Phys. Lett. A, 234, 1997, 336-344, doi:10.1016/S0375-9601(97)00598-7.
  2. H. Voss, P. Kolodner, M. Abel, and J. Kurths. Amplitude equations from spatiotemporal binary-fluid convection data. Phys. Rev. Lett., 83(17), 1999, 3422-3425,doi:10.1103/PhysRevLett.83.3422.
  3. N. Wessel, A. Voss, H. Malberg, Ch. Ziehmann, H. U. Voss, A. Schirdewan, U. Meyerfeldt, and J. Kurths. Nonlinear analysis of complex phenomena in cardiological data, Herzschr. Elektrophys., 11(3), 2000, 159-173, doi:10.1007/s003990070035.
  4. N. Marwan, N. Wessel, U. Meyerfeldt, A. Schirdewan, and J. Kurths. Recurrence Plot Based Measures of Complexity and its Application to Heart Rate Variability Data, Phys. Rev. E, 66(2), 2002, 026702, doi:10.1103/PhysRevE.66.026702.
  5. N. Marwan, M. Thiel, and N.R. Nowaczyk. Cross Recurrence Plot Based Synchronization of Time Series, Nonlin. Proc. Geophys., 9, 2002, 325-331, url:www.copernicus.org/EGU/npg/9/325.htm.
  6. N. Marwan and J. Kurths. Nonlinear analysis of bivariate data with cross recurrence plots, Phys. Lett. A, 302(5-6), 2002, 299-307, doi:10.1016/S0375-9601(02)01170-2.
  7. M. G. Rosenblum, L. Cimponeriu, A. Bezerianos, A. Patzak, and R. Mrowka. Identification of coupling direction: Application to cardiorespiratory interaction, Phys. Rev. E, 65, 2002, 041909, doi:10.1103/PhysRevE.65.041909.
  8. A. Sitz, U. Schwarz, J. Kurths, and H. U. Voss. Estimation of parameters and unobserved components for nonlinear systems from noisy time series, Phys. Rev. E, 66, 2002, 016210, doi:10.1103/PhysRevE.66.016210.
  9. D. Maraun and J. Kurths. Cross Wavelet Analysis. Significance Testing and Pitfalls, Nonlin. Proc. Geoph., 11, 2004, 505-514, url:www.copernicus.org/EGU/npg/11/4/505.htm.
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