TY - JOUR
T1 - Time-varying dimension analysis of EEG using adaptive principal component analysis and model selection
AU - Celka, P.
AU - Mesbah, M.
AU - Keir, M.
AU - Boashash, B.
AU - Colditz, P.
PY - 2000
Y1 - 2000
N2 - 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.
AB - 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.
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U2 - 10.1109/IEMBS.2000.898003
DO - 10.1109/IEMBS.2000.898003
M3 - Article
AN - SCOPUS:0034444596
SN - 1557-170X
VL - 2
SP - 1404
EP - 1407
JO - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
JF - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
ER -