Two-dimensional wavelet analysis based classification of gas chromatogram differential mobility spectrometry signals

Weixiang Zhao, Shankar Sankaran, Ana M. Ibáñez, Abhaya M. Dandekar, Cristina E Davis

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

This study introduces two-dimensional (2-D) wavelet analysis to the classification of gas chromatogram differential mobility spectrometry (GC/DMS) data which are composed of retention time, compensation voltage, and corresponding intensities. One reported method to process such large data sets is to convert 2-D signals to 1-D signals by summing intensities either across retention time or compensation voltage, but it can lose important signal information in one data dimension. A 2-D wavelet analysis approach keeps the 2-D structure of original signals, while significantly reducing data size. We applied this feature extraction method to 2-D GC/DMS signals measured from control and disordered fruit and then employed two typical classification algorithms to testify the effects of the resultant features on chemical pattern recognition. Yielding a 93.3% accuracy of separating data from control and disordered fruit samples, 2-D wavelet analysis not only proves its feasibility to extract feature from original 2-D signals but also shows its superiority over the conventional feature extraction methods including converting 2-D to 1-D and selecting distinguishable pixels from training set. Furthermore, this process does not require coupling with specific pattern recognition methods, which may help ensure wide applications of this method to 2-D spectrometry data.

Original languageEnglish (US)
Pages (from-to)46-53
Number of pages8
JournalAnalytica Chimica Acta
Volume647
Issue number1
DOIs
StatePublished - Aug 4 2009

Keywords

  • Differential mobility spectrometry
  • Gas chromatography
  • Pattern recognition
  • Principal component
  • Support vector machine
  • Wavelet

ASJC Scopus subject areas

  • Biochemistry
  • Analytical Chemistry
  • Spectroscopy
  • Environmental Chemistry

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