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With the bispec-tral index BIS a single parameter is used as input which represents a non-invasive measurement of the DOA. The standard model consists of a linear dynamic pharmacokinetic part and a nonlinear static pharmacodynamic part. On-line identification of the model parameters based on input-ouput measure-ments is desireable and may be achieved by nonlinear identification schemes. In the present paper the performance of artificial neural networks with a feedforward structure in the identification of both static nonlinearities and nonlinear dynamic physiological systems is investigated.

From these realizations it is evident that the neural networks are able to reproduce the system dynamics even in the presence of measurement noise. See more. Follow Us. Follow us on Facebook opens in a new window Follow us on Facebook opens in a new window Follow us on Twitch opens in a new window Follow us on Twitch opens in a new window Follow us on Twitter opens in a new window Follow us on Twitter opens in a new window Follow us on Youtube opens in a new window Follow us on Youtube opens in a new window.

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