| 复参数最小二乘估计方法 |
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| 引用本文： | 崔博文,陈剑,陈心昭,任章.复参数最小二乘估计方法[J].安徽大学学报(自然科学版),2005,29(3):5-10. |
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| 作者姓名： | 崔博文 陈剑 陈心昭 任章 |
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| 作者单位： | 合肥工业大学,机械与汽车工程学院,安徽,合肥,230009;集美大学,机械工程学院,福建,厦门,361021;合肥工业大学,机械与汽车工程学院,安徽,合肥,230009;北京航空航天大学,自动化与电气工程学院,北京,100083 |
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| 基金项目： | 国家自然科学基金;50275044; |
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| 摘 要： | 提出了基于复数U-D分解的复参数最小二乘估计方法。在传统的加权遗忘因子法的递推算法中,方差矩阵P(k)由于衰减很快而极易失去正定性.为了保证参数估计的收敛性,利用复数U-D分解,将方差矩阵P(k)进行U-D分解,将P(k)矩阵的递推计算已转化为U(k)和D(k)的递推计算问题,保证了数值计算的稳定性.
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| 关 键 词： | UD分解 复参数 最小二乘估计 |
| 文章编号： | 1000-2162(2005)03-0005-06 |
Least square method for complex estimation |
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| CUI Bo-Wen,CHEN Jian,Chen Xin-Zhao,Ren Zhang.Least square method for complex estimation[J].Journal of Anhui University(Natural Sciences),2005,29(3):5-10. |
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| Authors: | CUI Bo-Wen CHEN Jian Chen Xin-Zhao Ren Zhang |
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| Abstract: | The paper presents a new U-D factorization based least squares methods for complex estimation. In the conventional weighted recursive least squares algorithm with forgot factors for complex-domain data, the covariance matrix P(k) converges to zero as time index k tends toward infinity. In order to keep converge in parameters estimation, the covariance matrix P(k) is to be decomposed using U-D factorization of matrix, the recursive calculation of P(k) is turned to be recursive calculation of U(k) and D(k),and the stability of numerical calculation is maintained. |
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| Keywords: | U-D factorization complex-domain data least square estimation |
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