Parameter Identification of Dynamic Models Using a Bayes Approach
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摘要: 将统计分析中的Bayes方法应用到参数识别问题中,提出了利用测量频率的Bayes估计识别动力学模型的方法,该方法是基于广义逆特征值问题的解。考虑到试验数据的随机性,测量频率用正态分布来描述。此外,将工程师关于测量频率的置信度进行量化,并且与识别过程相结合。数值算例证明了这一方法的有效性。Abstract: The Bayesian method of statistical analysis has been applied to the parameter identification problem.A method is presented to identify parameters of dynamic models with the Bayes estimators of measurement frequencies.This is based on the solution of an inverse generalized eigenvalue problem.The stochastic nature of test date is considered and a normal distribution is used for the measurement frequencies.An additional feature is that the engineer's confidence in the measurement frequencies is quantified and incorporated into the identification procedure.A numerical example demonstrates the efficiency of the method.
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