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A Complex Generalized Gaussian Distribution— Characterization, Generation, and Estimation

机译:复杂的广义高斯分布—表征,生成和估计

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摘要

The generalized Gaussian distribution (GGD) provides a flexible and suitable tool for data modeling and simulation, however the characterization of the complex-valued GGD, in particular generation of samples from a complex GGD have not been well defined in the literature. In this correspondence, we provide a thorough presentation of the complex-valued GGD by: (i) constructing the probability density function (pdf); (ii) defining a procedure for generating random numbers from the complex-valued GGD; and (iii) implementing a maximum likelihood estimation (MLE) procedure for the shape and covariance parameters in the complex domain. We quantify the performance of the MLE with simulations and actual radar data.
机译:广义高斯分布(GGD)为数据建模和仿真提供了一种灵活而合适的工具,但是复值GGD的表征,尤其是从复杂GGD生成样本的文献还没有得到很好的定义。在此对应关系中,我们通过以下方式全面介绍了复数值GGD:(i)构建概率密度函数(pdf); (ii)定义从复值GGD生成随机数的程序; (iii)对复杂域中的形状和协方差参数执行最大似然估计(MLE)程序。我们通过仿真和实际雷达数据量化MLE的性能。

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