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Title: 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:
 [1];  [2]
  1. Philadelphia, TN
  2. Concord, TN
Issue Date:
Research Org.:
Oak Ridge National Lab. (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 G06K - RECOGNITION OF DATA
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 = {1998},
month = {1}
}

Works referenced in this record:

The analysis of observed chaotic data in physical systems
journal, October 1993


Independent coordinates for strange attractors from mutual information
journal, February 1986


Extracting qualitative dynamics from experimental data
journal, June 1986


Phase Space Analysis of Human EEG during General Anesthesia
journal, July 1987


Nonlinear time Sequence Analysis
journal, September 1991