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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 are disclosed. 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. 8 figs.

Inventors:
;
Issue Date:
Research Org.:
Lockheed Martin Energy Research Corporation
Sponsoring Org.:
USDOE, Washington, DC (United States)
OSTI Identifier:
672692
Patent Number(s):
5,815,413
Application Number:
PAN: 8-853,226
Assignee:
Lockheed Martin Energy Research Corp., Oak Ridge, TN (United States) PTO; SCA: 990200; 320303; PA: EDB-98:124024; SN: 98002026807
DOE Contract Number:  
AC05-96OR22464
Resource Type:
Patent
Resource Relation:
Other Information: PBD: 29 Sep 1998
Country of Publication:
United States
Language:
English
Subject:
99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; NONLINEAR PROBLEMS; TIME-SERIES ANALYSIS; ON-LINE MEASUREMENT SYSTEMS; PROCESS CONTROL; DATA ACQUISITION; DIGITIZERS

Citation Formats

Hively, L.M., and Ng, E.G. Integrated method for chaotic time series analysis. United States: N. p., 1998. Web.
Hively, L.M., & Ng, E.G. Integrated method for chaotic time series analysis. United States.
Hively, L.M., and Ng, E.G. Tue . "Integrated method for chaotic time series analysis". United States.
@article{osti_672692,
title = {Integrated method for chaotic time series analysis},
author = {Hively, L.M. and Ng, E.G.},
abstractNote = {Methods and apparatus for automatically detecting differences between similar but different states in a nonlinear process monitor nonlinear data are disclosed. 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. 8 figs.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1998},
month = {9}
}