Advantage of the proposed algorithm is that any source can be separated, whether it is super-Gaussian or sub-Gaussian signal.
该算法可以对任意源信号进行分离，而不管它是超高斯还是亚高斯信号。
Some cross-cumulant-based algorithms can't recover sources from the mixtures of super-Gaussian, sub-Gaussian and Gaussian signals.
有些基于互累积量准则的算法不能够分离超高斯、亚高斯与高斯信号的混合信号。
The feasibility of the method was testified by the separation experiment of the mixed vibration signals, mixed sub-gaussian and super gaussian signals.
最后分别用亚高斯、超高斯的混合信号和振动混合信号的分离试验验证了该方法的可行性。
A supervised image segmentation algorithm is proposed, which is based on Gaussian statistical property of sub-regions obtained by watershed segmentation.
在分水岭分割的基础上，利用子区域像素值的高斯统计性质，提出了一种有监督的图像背景学习方法。
A supervised image segmentation algorithm is proposed, which is based on Gaussian statistical property of sub-regions obtained by watershed segmentation.
在分水岭分割的基础上，利用子区域像素值的高斯统计性质，提出了一种有监督的图像背景学习方法。
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