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Two improvements of early transition detection
Author(s) -
Marth M.,
Maier D.,
Honerkamp J.,
Goschnick J.
Publication year - 1999
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/(sici)1099-128x(199909/10)13:5<525::aid-cem560>3.0.co;2-c
Subject(s) - transition (genetics) , computer science , change detection , pattern recognition (psychology) , artificial intelligence , data mining , chemistry , biochemistry , gene
Two improvements of early transition detection (ETD) are presented. One improvement allows for transitions to be detected if they occur on very different timescales. The other extends ETD to be applicable together with unsupervised classification methods. Both improvements are successfully tested on data obtained from sensor array measurements. Copyright © 1999 John Wiley & Sons, Ltd.