Information criteria determine the number of active sources

T.R. Knosche, T.R. Knosche, E.M. Berends, M.J. Peters, Bert Jagers

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    With the neuroelectromagnetic inverse problem, the optimal choice of the number of sources is a difficult problem, especially in the presence of correlated noise. In this paper we present a number of information criteria that help to solve this problem. They are based on the probability density function of the measurements or their eigenvalues. Make use of the Akaike or MDL (minimum description length) correction term and all employ some sort of noise information. By extensive simulations we investigated the conditions under which these criteria yield reliable estimations. We were able to quantify two major factors of influence: (1) the precision of the noise information and (2) the signal-to-noise ratio (SNR). Here defined as the ratio of the smallest signal eigenvalues and the average of the noise eigenvalues. Furthermore, we found that the Akaike correction term tends to overestimate, due to its greater sensibility to the precision of the noise information
    Original languageUndefined
    Title of host publicationProc. of the IBME
    Place of PublicationArnhem
    Number of pages5
    ISBN (Print)90-365-0845-2
    Publication statusPublished - 30 Sep 1996
    Event18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 1996: Bridging Disciplines for Biomedicine - Amsterdam, Netherlands
    Duration: 31 Oct 19963 Nov 1996
    Conference number: 18

    Publication series



    Conference18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 1996
    Abbreviated titleEMBC


    • IR-56014
    • METIS-130341

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