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The efficiency of feature feedback using R-LDA with application to portable E-Nose system

  • Lang Bach Truong
  • , Sang Il Choi
  • , Yoonseok Yang
  • , Young Dae Lee
  • , Gu Min Jeong*
  • *Corresponding author for this work

Research output: Contribution to conferenceConference paperpeer-review

Abstract

In this paper, we improve the performance of Feature Feedback and present its application for vapor classification in a portable E-Nose system. Feature Feedback is a preprocessing method which detects and removes unimportant information from input data so that classification performance is improved. In our original Feature Feedback algorithm, PCA is used before LDA in order to avoid the small sample size (SSS) problem but it is said that this may cause loss of significant discriminant information for classification. To overcome this, in the proposed method, we improve Feature Feedback using regularized Fisher's separability criterion to extract the features and apply it to E-Nose system. The experimental result shows that the proposed method works well.

Original languageEnglish
Title of host publicationMultimedia, Computer Graphics and Broadcasting - Int. Conf. MulGraB 2011, Held as Part of the Future Generation Information Technology Conf. FGIT 2011, in Conjunction with GDC 2011, Proc.
Pages316-323
Number of pages8
EditionPART 1
DOIs
StatePublished - 2011
Event2011 International Conference on Multimedia, Computer Graphics and Broadcasting, MulGraB 2011, Held as Part of the 3rd International Mega-Conference on Future-Generation Information Technology, FGIT 2011, in Conjunction with GDC 2011 - Jeju Island, Korea, Republic of
Duration: 2011.12.82011.12.10

Publication series

NameCommunications in Computer and Information Science
NumberPART 1
Volume262 CCIS
ISSN (Print)1865-0929

Conference

Conference2011 International Conference on Multimedia, Computer Graphics and Broadcasting, MulGraB 2011, Held as Part of the 3rd International Mega-Conference on Future-Generation Information Technology, FGIT 2011, in Conjunction with GDC 2011
Country/TerritoryKorea, Republic of
CityJeju Island
Period11.12.811.12.10

Keywords

  • discriminant feature
  • e-nose system
  • feature feedback
  • vapor classification

Quacquarelli Symonds(QS) Subject Topics

  • Computer Science & Information Systems
  • Mathematics

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