Symbolic dynamics of wavelet images for pattern identification

Xin Jin, Shalabh Gupta, Kushal Mukherjee, Asok Ray

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Symbolic time series analysis has been introduced in recent literature for pattern identification in dynamical systems. Relevant information, embedded in the measured time series, is extracted in the form of symbol sequences by partitioning of the data sets, and probabilistic finite state automata are constructed from these symbol sequences to generate pattern vectors. This paper presents a symbolic pattern identification method by partitioning of two-dimensional wavelet (i.e., scale-shift) images of sensor time series data. The proposed method is experimentally validated on a laboratory apparatus for identification of evolving patterns due to fatigue damage in polycrystalline alloy specimens.

Original languageEnglish (US)
Title of host publicationProceedings of the 2010 American Control Conference, ACC 2010
Pages3481-3486
Number of pages6
StatePublished - 2010
Event2010 American Control Conference, ACC 2010 - Baltimore, MD, United States
Duration: Jun 30 2010Jul 2 2010

Publication series

NameProceedings of the 2010 American Control Conference, ACC 2010

Other

Other2010 American Control Conference, ACC 2010
Country/TerritoryUnited States
CityBaltimore, MD
Period6/30/107/2/10

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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