Predictable nonlinear dynamics: Advances and limitations
- Vladimir Cardiological Center, Vladimir 600023 (Russia)
- Vladimir Technical University, Vladimir, 600029 (Russia)
- Space Research Inst, Russian Acad. Sci., Moscow 117810 (Russia)
- Moscow State Pedagogical Univ., Moscow, 119485 (Russia)
Methods for reconstruction chaotic dynamical system structure directly from experimental time series are described. Effectiveness of general methods is illustrated with the results of numerical simulation. It is of common interest that from the single time series it is possible to reconstruct a set of interconnected variables. Predictive power of dynamical models, provided by the nonlinear dynamics inverse problem solution, is limited firstly by the noise level in the system under study and is characterized by the horizon of predictability. New physical results are presented, concerning nonstationary and bifurcation nonlinear systems: (1) algorithms for revealing of nonstationarity in random-like chaotic time-series are suggested based on discriminant analysis with nonlinear discriminant function; (2) an opportunity is established to predict the final state in bifurcation system with quickly varying control parameters; (3) hysteresis is founded out in bifurcation system with quickly varying parameters; (4) delayed correlation {l_angle}noise-prediction error{r_angle} in chaotic systems is revealed. {copyright} {ital 1996 American Institute of Physics.}
- OSTI ID:
- 401074
- Report Number(s):
- CONF-950730-; ISSN 0094-243X; TRN: 96:029451
- Journal Information:
- AIP Conference Proceedings, Vol. 375, Issue 1; Conference: 3. technical conference on nonlinear dynamics (chaos) and full spectrum processing, Mystic, CT (United States), 10-13 Jul 1995; Other Information: PBD: Jun 1996
- Country of Publication:
- United States
- Language:
- English
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