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NONLINEAR TIME SEQUENCE ANALYSIS
Abstract
We review several aspects of the analysis of time sequences, and concentrate on recent methods using concepts from the theory of nonlinear dynamical systems. In particular, we discuss problems in estimating attractor dimensions, entropies, and Lyapunov exponents, in reducing noise and in forecasting. For completeness and since we want to stress connections to more traditional (mostly spectrum-based) methods, we also give a short review of spectral methods.
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Cited by
Physiological time-series analysis using approximate entropy and sample entropy
Richman, J. S., & Moorman, J. R. (2000) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.2000.278.6.h2039 · Cited by 7,880
Andrzejak, R. G., Lehnertz, K., Mormann, F., Rieke, C., David, P., & Elger, C. E. (2001) · Physical Review E · doi:10.1103/physreve.64.061907 · Cited by 3,032
Multiscale entropy analysis of biological signals
Costa, M., Goldberger, A. L., & Peng, C.-K. (2005) · Physical Review E · doi:10.1103/physreve.71.021906 · Cited by 2,482
Metadata
- Authors
- GRASSBERGER, P., SCHREIBER, T., & SCHAFFRATH, C.
- Venue
- International Journal of Bifurcation and Chaos
- Publisher
- World Scientific Pub Co Pte Lt
- Published
- 1991-09
- Volume
- 01
- Issue
- 03
- Pages
- 521-547
- ISSN
- 0218-1274 (ISSN-L)
- 1793-6551
- OpenAlex
- W2007979658
- Cited by
- 526
- References
- 0
- FWCI
- 18.91
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: NONLINEAR TIME SEQUENCE ANALYSIS. https://app.cochat.ai/papers/10.1142/s0218127491000403
- The paper
- GRASSBERGER, P., SCHREIBER, T., & SCHAFFRATH, C. (1991). NONLINEAR TIME SEQUENCE ANALYSIS. International Journal of Bifurcation and Chaos. https://doi.org/10.1142/s0218127491000403
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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