首页> 外文会议>1995 IEEE engineering in medicine and biology 17th annual conference and 21st Canadian medical and biological engineering conference >Error Analysis in Parameter Estimation of Physiological Systems with Uncertain Model Inputs and Assigned Model Constants
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Error Analysis in Parameter Estimation of Physiological Systems with Uncertain Model Inputs and Assigned Model Constants

机译:具有不确定模型输入和指定模型常数的生理系统参数估计中的误差分析

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Mathematical models of physiological systems often include model parameters and inputs that are considered as known, e.g. from measurements, and that are assigned as constants in the identification/parameter estimation process. Usually, assigned variables are considered error-free but uncertainty in their value affects estimation precision of the remaining parameters. This problem is addressed in this paper for dynamic models described by non-linear ordinary differential equations and for non-linear weighted least squares parameter estimation. The theory is applied to a model of glucose disappearance for quantifying the individual contribution of various error sources.
机译:生理系统的数学模型通常包括模型参数和输入,这些参数和输入被认为是已知的。从测量中获取,并在识别/参数估计过程中将其分配为常量。通常,分配的变量被认为是无差错的,但是其值的不确定性会影响其余参数的估算精度。本文针对非线性常微分方程描述的动态模型以及非线性加权最小二乘参数估计解决了该问题。该理论被应用于葡萄糖消失模型,以量化各种误差源的个体贡献。

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