复值型数据Improper线性回归模型的估计
收稿日期: 2011-03-11
修回日期: 2011-04-02
网络出版日期: 2012-03-15
基金资助
Supported by National Natural Science Foundation of China (10801133) and President Foundation of GUCAS
Estimations of the improper linear regression models with complex-valued data
Received date: 2011-03-11
Revised date: 2011-04-02
Online published: 2012-03-15
Supported by
Supported by National Natural Science Foundation of China (10801133) and President Foundation of GUCAS
闫长君 , 张三国 , 宁炜 . 复值型数据Improper线性回归模型的估计[J]. 中国科学院大学学报, 2012 , (2) : 145 -153 . DOI: 10.7523/j.issn.2095-6134.2012.2.001
A complex-valued random variable is improper if its complementary covariance is not 0, otherwise it is proper. In this paper, we consider the linear regression models whose errors are independent and identically distributed following an improper complex Gaussian distribution. Such a model may be encountered in signal processing. We use the maximum likelihood method and the two-stage least squares method to estimate the regression coefficients. Differences between these two methods and the complex version of least squares estimates are investigated by simulations. A wind data set is used to illustrate the proposed approach.
Key words： complex-valued data; improper; complex Gaussian distribution
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