NeuroSpectraNet - a self-organising neural network mechanism for interpretation of complex SSIMS spectra

O D Sanni, A Henderson, D Briggs, J C Vickerman

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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    Abstract

    NeuroSpectraNet demonstrated that neural processing power can be harnessed for anal. of SSIMS spectra. If a spectrum similar to an unknown exist in NeuroSpectraNet's database, it would efficiently and correctly identify the unknown in a matter of seconds. If an unknown is so unique that it is completely new to NeuroSpectraNet's self-organizing mechanism, NeuroSpectraNet is designed to help the analyst to correctly identify predefined functionalities that may be present in the unknown. Because the anal. is fast and reliable, the spectrometrist can focus his attention on more complex tasks better armed. [on SciFinder (R)]
    Original languageEnglish
    Title of host publicationSecond. Ion Mass Spectrom., SIMS XII, Proc. Int. Conf., 12th
    Pages805-808
    Number of pages4
    Publication statusPublished - 2000

    Keywords

    • Simulation and Modeling (neural network
    • NeuroSpectraNet - self-organizing neural network mechanism for interpretation of complex SSIMS spectra)
    • Secondary-ion mass spectrometry (static
    • neuroSpectraNet organizing neural network static SIMS

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