Abstract
We present a method based on dynamical systems theory which can be used to filter time series in a way which is superior to classical Fourier decomposition. This method is applied to three data-sets, taken from respiratory measurements of two children in quiet and REM sleep. Our purpose is to filter the several different oscillatory mechanisms which operate, in order to provide clearer signals on which further analysis and diagnosis can be based.
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