G. Kember

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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(More)
We show how the use of " smart " embeddings of time series can indicate the presence of (large) delay in a system, and how they can be used to enhance predictions based on nonlinear dynamics methods. 1. Delay equations are of wide relevance to natural x=f(x 1) [7], but the rapid oscillations make any dynamical systems, particularly in medicine and such easy(More)
The performances of two MPC (model predictive control) techniques, move-suppressed and shifted, are studied under normally distributed random communication delays to test the potential of MPC as a control method over the Internet. A conventional PID is also implemented under the same delay conditions. All controls are run in a time-scheduling scheme. The(More)
The recent application of methods from nonlinear systems theory to the analysis of time series can be used to provide a novel technique for filtering such series, when they represent the coupled output of several distinct oscillators. The method is a nonlinear analogue of Fourier spectral analysis, but is potentially more powerful, in that it allows for(More)
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