NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Classification of ion mobility spectra by functional groups using neural networksNeural networks were trained using whole ion mobility spectra from a standardized database of 3137 spectra for 204 chemicals at various concentrations. Performance of the network was measured by the success of classification into ten chemical classes. Eleven stages for evaluation of spectra and of spectral pre-processing were employed and minimums established for response thresholds and spectral purity. After optimization of the database, network, and pre-processing routines, the fraction of successful classifications by functional group was 0.91 throughout a range of concentrations. Network classification relied on a combination of features, including drift times, number of peaks, relative intensities, and other factors apparently including peak shape. The network was opportunistic, exploiting different features within different chemical classes. Application of neural networks in a two-tier design where chemicals were first identified by class and then individually eliminated all but one false positive out of 161 test spectra. These findings establish that ion mobility spectra, even with low resolution instrumentation, contain sufficient detail to permit the development of automated identification systems.
Document ID
20040089036
Document Type
Reprint (Version printed in journal)
Authors
Bell, S. (Eastern Washington University Cheney 99004, United States)
Nazarov, E.
Wang, Y. F.
Eiceman, G. A.
Date Acquired
August 21, 2013
Publication Date
January 1, 1999
Publication Information
Publication: Analytica chimica acta
Volume: 394
ISSN: 0003-2670
Subject Category
Life Sciences (General)
Funding Number(s)
CONTRACT_GRANT: NAGY4-558
CONTRACT_GRANT: DAAH04-95-1-0541
Distribution Limits
Public
Copyright
Other
Keywords
Non-NASA Center
NASA Discipline Environmental Health