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 引用本文: 陈增强, 林茂琼, 袁著祉. 递推阻尼最小二乘法的收敛性与稳定性[J]. 应用数学和力学, 2000, 21(2): 209-214.
Chen Zengqiang, Lin Maoqiong, Yuan Zhuzhi. Convergence and Stability of Recursive Damped Least Square Algorithm[J]. Applied Mathematics and Mechanics, 2000, 21(2): 209-214.
 Citation: Chen Zengqiang, Lin Maoqiong, Yuan Zhuzhi. Convergence and Stability of Recursive Damped Least Square Algorithm[J]. Applied Mathematics and Mechanics, 2000, 21(2): 209-214.

递推阻尼最小二乘法的收敛性与稳定性

作者简介:陈增强(1964~ ),男,天津人,教授,工学博士.
• 中图分类号: O231;O241

Convergence and Stability of Recursive Damped Least Square Algorithm

• 摘要: 递推最小二乘法是参数辨识中最常用的方法,但容易产生参数爆发现象.因此对一种更稳定的辨识方法——递推阻尼最小二乘法进行了收敛特性的分析.在使用算法之前先归一化测量向量,结果表明,参数化距离收敛于一个零均值随机变量,并且在持续激励条件下,适应增益矩阵的条件数有界.参数化距离的方差有界.
•  [1] Goodwin G C.Adaptive Filtering Prediction and Control[M].Englewood Cliffs:Prentice Hall,1984. [2] Lozanno R.Convergence analysis of recursive identification algorithms with forgetting factor[J].Automatica,1983,19(1):95～97. [3] Ljung L.Analysis of a general recursive prediction error identification algorithm[J].Automatica,1981,17(1):89～99. [4] Spripada N R,Fisher D G.Improved least squares identification[J].Internat J Control,1987,46(6):1889～1913. [5] Levenberg K.A method for the solution of certain non-linear problems in least squares[J].Quart Appl Math,1944,26(2):164～168.
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出版历程
• 收稿日期:  1998-09-03
• 修回日期:  1999-01-04
• 刊出日期:  2000-02-15

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