Time-varying dimension analysis of EEG using adaptive principal component analysis and model selection

P. Celka, M. Mesbah, M. Keir, B. Boashash, P. Colditz

نتاج البحث: المساهمة في مجلةمراجعة النظراء

3 اقتباسات (Scopus)

ملخص

This paper present a new approach to the analysis of non-stationary possibly nonlinear time series. It is based on an adaptive autocorrelation eigenspectrum computation known as APEX together with a model selection rule. New concepts of stochastic instantaneous embedding dimension and time averaged instantaneous embedding dimension are introduced. The motivation for this new approach is the analysis of newborn electroencephalogram for which non-stationarity is a crutial property. Experimental data are analyzed using the proposed scheme.

اللغة الأصليةEnglish
الصفحات (من إلى)1404-1407
عدد الصفحات4
دوريةAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
مستوى الصوت2
المعرِّفات الرقمية للأشياء
حالة النشرPublished - 2000
منشور خارجيًانعم

ASJC Scopus subject areas

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بصمة

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