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A hybrid method for parameter estimation and its application to biomedical systems.

机译:一种用于参数估计的混合方法及其在生物医学系统中的应用。

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摘要

A general version of a hybrid method for parameter estimation is presented with a theoretical support and an illustrative example of application. This method consists of a curve fitting algorithm that takes the initial estimate of the parameterization from an artificial neural network. The idea is to improve the convergence of the algorithm to the sought parameterization using a close initial estimate. The motivation arises from biomedical problems where one is interested in obtaining a meaningful estimate so that it can be used for both description and prediction purposes. Two strategies are proposed for the application of the hybrid method: one is of general applicability, the other is intended for systems defined by the series connection of various blocks. The feasibility of the method is illustrated with a case study related to the neuromuscular blockade of patients undergoing general anaesthesia.
机译:提出了用于参数估计的混合方法的一般版本,并提供了理论支持和应用示例。该方法由曲线拟合算法组成,该算法从人工神经网络获取参数化的初始估计。这个想法是使用一个接近的初始估计来改善算法到所寻找的参数化的收敛性。动机来自生物医学问题,其中人们有兴趣获得有意义的估计,以便可以将其用于描述和预测目的。对于混合方法的应用,提出了两种策略:一种是通用的,另一种是针对由各种模块的串联连接定义的系统的。通过与全麻患者神经肌肉阻滞相关的案例研究,说明了该方法的可行性。

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