基于非对称广义高斯模型的局部优化检测中的应用

为了在非高斯的情况下优化信号的检测，笔者致力于提供一种通用的噪声概率密度函数的现实模型．这个模型仅仅依赖于几个容易且能快速估计的参数，还能够适应于诸如对称和非对称，以及带有不同锐利程度的不同噪声．为了达到这个目的，一种来源于广义高斯函数的高阶统计量的模型被提出，它依赖于3个参数：表示不同锐利程度的峰度参数，以及描写不同于对称函数且联合提供偏斜程度的左右方差参数．这个模型在局部优化检测的设计中得到很好运用，被水下声学噪声干扰的信号检测证实了这个结果．

Application to Locally Optimum Detection Based on Asymmetric Generalized Gaussian distribution

The work is dedicated to provide modeling of a generic noise probability function(PDF),in order to optimize signal detection in non-Gaussian environments.The model only depends on a few parameters which can be estimated easily and quickly,and can be adapted to many kinds of noise such as symmetric or asymmetric or with variable sharpness.At the end,we presented a new high order statistic model which derives from the generalized Gaussian function and depends on three parameters: kurtosis,for representing var...