Resumen
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.
| Idioma original | English |
|---|---|
| Páginas (desde-hasta) | 523-526 |
| Número de páginas | 4 |
| Publicación | Canadian Conference on Electrical and Computer Engineering |
| Volumen | 1 |
| Estado | Published - 1995 |
| Evento | Proceedings of the 1995 Canadian Conference on Electrical and Computer Engineering. Part 1 (of 2) - Montreal, Can Duración: sep. 5 1995 → sep. 8 1995 |
ASJC Scopus Subject Areas
- Hardware and Architecture
- Electrical and Electronic Engineering
Huella
Profundice en los temas de investigación de 'Nonlinear open-loop gain of the baroreflex using artificial feedforward neural networks'. En conjunto forman una huella única.Citar esto
Larchie, I., Nugent, S. T., & Finley, J. P. (1995). Nonlinear open-loop gain of the baroreflex using artificial feedforward neural networks. Canadian Conference on Electrical and Computer Engineering, 1, 523-526.