Integrated method for chaotic time series analysis
Abstract
Methods and apparatus for automatically detecting differences between similar but different states in a nonlinear process monitor nonlinear data. Steps include: acquiring the data; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; and determining by comparison whether differences between similar but different states are indicated.
- Inventors:
-
- Philadelphia, TN
- Concord, TN
- Issue Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- OSTI Identifier:
- 871874
- Patent Number(s):
- 5815413
- Assignee:
- Lockheed Martin Energy Research Corporation (Oak Ridge, TN)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06F - ELECTRIC DIGITAL DATA PROCESSING
- DOE Contract Number:
- AC05-96OR22464
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- integrated; method; chaotic; time; series; analysis; methods; apparatus; automatically; detecting; differences; similar; nonlinear; process; monitor; data; steps; acquiring; digitizing; obtaining; measures; via; serial; trends; determining; comparison; indicated; nonlinear measures; automatically detecting; analysis methods; time series; analysis method; serial trends; time serial; via chaotic; obtaining time; obtaining nonlinear; series analysis; chaotic time; data via; automatically detect; /702/600/
Citation Formats
Hively, Lee M, and Ng, Esmond G. Integrated method for chaotic time series analysis. United States: N. p., 1998.
Web.
Hively, Lee M, & Ng, Esmond G. Integrated method for chaotic time series analysis. United States.
Hively, Lee M, and Ng, Esmond G. Thu .
"Integrated method for chaotic time series analysis". United States. https://www.osti.gov/servlets/purl/871874.
@article{osti_871874,
title = {Integrated method for chaotic time series analysis},
author = {Hively, Lee M and Ng, Esmond G},
abstractNote = {Methods and apparatus for automatically detecting differences between similar but different states in a nonlinear process monitor nonlinear data. Steps include: acquiring the data; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; and determining by comparison whether differences between similar but different states are indicated.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jan 01 00:00:00 EST 1998},
month = {Thu Jan 01 00:00:00 EST 1998}
}
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.
Works referenced in this record:
G. A. Korn, and T. M. Korn, Mathematical Handbook for Scientists and Engineers. XVII + 1130 S. m. Fig. u. Tab. New York/San Francisco/Toronto/London/Sydney 1968. McGraw-Hill Book Company. Preis geb. $ 25.00
journal, January 1969
- Heinrich, H.
- ZAMM - Zeitschrift für Angewandte Mathematik und Mechanik, Vol. 49, Issue 9
The analysis of observed chaotic data in physical systems
journal, October 1993
- Abarbanel, Henry D. I.; Brown, Reggie; Sidorowich, John J.
- Reviews of Modern Physics, Vol. 65, Issue 4
Independent coordinates for strange attractors from mutual information
journal, February 1986
- Fraser, Andrew M.; Swinney, Harry L.
- Physical Review A, Vol. 33, Issue 2
Extracting qualitative dynamics from experimental data
journal, June 1986
- Broomhead, D. S.; King, Gregory P.
- Physica D: Nonlinear Phenomena, Vol. 20, Issue 2-3
Phase Space Analysis of Human EEG during General Anesthesia
journal, July 1987
- Watt, Richard C.; Hameroff, Stuart R.
- Annals of the New York Academy of Sciences, Vol. 504, Issue 1 Perspectives
Nonlinear time Sequence Analysis
journal, September 1991
- Grassberger, Peter; Schreiber, Thomas; Schaffrath, Carsten
- International Journal of Bifurcation and Chaos, Vol. 01, Issue 03