Résumé
The baroreflex control system is inherently nonlinear. Clinical measurements which rely on linear models provide adequate representation of the system as long as the input perturbations to the reflex loop are small and fall within the linear region of the response curve. We propose a novel technique that combines the approximation power of a class of artificial neural network(ANN), Volterra nonlinear block representation and eigen-analysis to provide estimates of the open-loop gain of the baroreflex. A range of eigen-parameters are extracted from the converged weight matrices of the ANN to provide a range of possible values of the gain factor of simulated baroreflex response curve.
Langue d'origine | English |
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Pages (de-à) | 523-526 |
Nombre de pages | 4 |
Journal | Canadian Conference on Electrical and Computer Engineering |
Volume | 1 |
Statut de publication | Published - 1995 |
Événement | Proceedings of the 1995 Canadian Conference on Electrical and Computer Engineering. Part 1 (of 2) - Montreal, Can Durée: sept. 5 1995 → sept. 8 1995 |
ASJC Scopus Subject Areas
- Hardware and Architecture
- Electrical and Electronic Engineering