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General模型辅助变量辨识方法的研究 被引量:1

Research of instrumental variable identification method for general models
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摘要 对于存在相关噪声干扰的General系统,研究了一种新的辨识方法。首先系统模型用一个有限的脉冲响应(FIR)模型逼近,得到一个Box-Jenkins模型,再使用辅助变量法辨识系统参数,最后根据模型等价原理确定原系统的参数估计。仿真结果表明:在这种近似下递推辅助变量法(RIV)比递推广义增广最小二乘法(RGELS)可以得到更好的参数估计。 For General model system of existing correlated interferential noise, this paper researches on a new method of identification, first of all system model is approximated by using to FIR model , and to obtain a Box-Jenkins model which can be identified by the Instrumental Variable method, and finally to determine the parameters of the original systems by means of the model equivalence principle. The simulation results indicate that Recursive Instrumental Variable (RIV) method has better parameter estimation than Recursive Generalized Extended Least Squares (RGELS) in this approximation.
作者 刘淑霞 黄敏
出处 《计算机工程与应用》 CSCD 北大核心 2008年第14期54-56,共3页 Computer Engineering and Applications
关键词 General模型 递推广义增广最小二乘 辅助变量法 参数估计 General model recursive generalized extended least squares Instrumental Variable parameter estimation
作者简介 刘淑霞(1981-),女,硕士研究生,主要从事系统辨识方面关于有色噪声的研究; 黄敏(1974-),女,副教授,博士,硕上生导师.
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