New method to obtain the power spectra of hidden variables and its application to ocean data

Wei en-bo; Tian Ji-wei; Xu Jin-shan

doi:10.1007/BF02842786

Your Location：

Home >

Browse articles >

New method to obtain the power spectra of hidden variables and its application to ocean data

Updated：2023-05-16

- New method to obtain the power spectra of hidden variables and its application to ocean data
- Journal of Oceanology and Limnology Vol. 19, Issue 1, Pages: 29-34(2001)
- Affiliations：
  
  1. College of Power Engineering University of Shanghai for Science and Technology
  2. Physical Oceanography Laboratory Ocean University of Qingdao
- Author bio：
- Funds：
- DOI：10.1007/BF02842786
  CLC：
- Published：2001
- Accepted：
Scan QR Code
en-bo, W., Ji-wei, T. & Jin-shan, X. New method to obtain the power spectra of hidden variables and its application to ocean data., Chin. J. Ocean. Limnol. 19, 29–34 (2001). https://doi.org/10.1007/BF02842786
DOI：

en-bo, W., Ji-wei, T. & Jin-shan, X. New method to obtain the power spectra of hidden variables and its application to ocean data., Chin. J. Ocean. Limnol. 19, 29–34 (2001). https://doi.org/10.1007/BF02842786 DOI：

摘要

Abstract

A novel method is proposed to obtain the power spectra of hidden variables in a chaotic time series. By embedding the data in phase space

and recording the conditional probability density of points that the trajectory encounters as it evolves in the reconstructed phase space

it is possible to recover the power spectra of hidden variables in chaotic time series through a spectral analysis over the conditional probability density time series. The method is robust in the application to Lorenz system

4-dimension Rössler system and rigid body motion by linear feedback system (LFRBM). Applying the method to the time series of sea surface temperature (SST) of the South China Sea

we obtained the power spectra of the wind speed (WS) from SST data. Furthermore

the results showed that there exists an important nonlinear interaction between the SST and the WS.

关键词

Keywords

references

Barahona, M., Poon, C. S., 1996. Detection of nonlinear dynamics in short, noisy time series.Nature 38: 215–217.

Ding, M., Grebogi, C., Ott, E. et al., 1993. Estimating correlation dimension from a chaotic time series: when does a plateau onset occur?Physica D 69: 404–424.

Eckmann, J. P., Ruelle, D., 1985. Ergodic theory of chaos and strange attractors.Rev. Mod. Phys. 57: 617–655.

Fraser, A.M., Swinney, H. L., 1986. Independent coordinates for strange attractors from mutual information.Phys. Rev. A 33: 1134–1140.

Grassberger, P., Procaccia, I., 1984. Dimensions and entropies of strange attractors from mutual information.Phys. Rev. A 33: 1134–1140.

Grassberger, P., Procaccia, I., 1984. Dimensions and entropies of strange attractors from a fluctuating dynamics approach.Physica D 13: 34–54.

Kennel, M. B., Brown, R., Abarbanel, H. D. I., 1992. Determining embedding dimension for phase space reconstruction using a geometrical construction.Phys. Rev. A 45: 3403–3411.

Kugiumtzis, D., 1996. State space reconstruction parameters in the analysis of chaotic time series: the role of the time window length.Phys. D 95: 13–28.

Lai Yingcheng, Lerner, D., Hayden, R., 1996. An upper bound for the proper delay time in chaotic time series analysis.Phys. Lett. A 218: 30–34.

Leipnik, R. B., Newton, T. A., 1981. Double strange attractor in rigid body motion with linear feedback control.Phys. Lett. A 86: 63–67.

Lipton J. M., Dabke, K. P., 1996. Reconstructing the state space of continuous time chaotic system using power spectra.Phys. Lett. A 210: 290–300.

Lorenz, E. N., 1963. Deterministic nonperiodic flow.J. Atmos. Sci. 20: 130–141.

Lanuca, R., Savit, R., 1996. Model misspecification tests, model building and predictability in complex systems.Physica D 93: 78–100.

Ortega, G., 1995. A new method to detect hidden frequencies in chaotic time series.Phys. Lett. A 209: 351–355.

Packard, N. H., Crutchfield, J. P., Farmer, J. D., et al., 1980. Geometry from a time series.Phys. Rev. Lett. 45: 712–716.

Rössler, O. E., 1979. An equation for hyperchaos.Phys. Lett. A 71: 155–157.

Takens, F., 1980. Lecture notes in mathematics, 1981. Dynamical Systems and Turbulence, Warwick.In: Rand D. A., Young L. S. eds, Springer, Berlin,898: 366–381.

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

No data

Related Author

No data

Related Institution

No data

Address：Editorial Office of JOL, 88 Haijun Rd. Qingdao, 266000, China
Tel：+86-532-82898754 Email：jol@qdio.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09064830号-19 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰