The result of simulation showed that: 1) the non-Gaussian degrees of the three non-Gaussiandistributions mentioned above are different with each other;
实验结果表明：上述三种非高斯分布的非高斯程度不同；
2
Examples on the application of this algorithm are also given for estimating the parameters of the mixtures of M(M is a posivive integer) univariate Gaussiandistributions.
文中给出了利用这种估计法对多分量混合一元高斯分布进行参数估计的实例。
3
And the weight of each filter is updated using Bayes theory based on the assumption that the difference between estimate and measurement bearings obeys Gaussiandistributions with zero mean error.