本文利用高斯分解法给出了聚焦光学系统中光学非线性介质引起的光学限制效应，以及几何排布对其的影响。
This paper presents the optical limiting and its dependence of the geometrical arrangement in the focused optical system by employing the Gaussian decomposition method.
浮点数表示法，含部份换轴之高斯消去法，使用矩阵大小之计算尺度调整，带状及三角对角系统，LU分解。
Floating point representation, Gaussian elimination with partial pivoting, scaling of computations with matrix size, banded and tri-diagonal systems, LU decomposition.
提出了一种基于高斯金字塔分解的数字图像扩频水印技术。
In this paper, a spread spectrum digital watermark based on Gaussian pyramid decomposition was proposed.
采用矩阵分解的方法，从柯林斯衍射积分公式出发，对高斯光束通过失调空间滤波器的传输特性进行了分析，得到了相应的解析式。
Based on the method of matrix decomposition, and the Collins diffraction integral formulae, the propagation characteristics of a Gaussian beams passing through misaligned spatial filter are studied.
在水印算法中用奇异值分解可以提高图像的抗几何失真性，但它对椒盐、高斯、滤波等攻击的抵抗能力却很弱。
Use singular value decomposition (SVD) in the watermark algorithm may enhance the anti-geometry distortion of the image, but it is very weak to some attacks such as salt, gauss, filter and etc.
对四阶累量混合波达方向矩阵进行特征分解，可实现有色高斯噪声背景中空域信号二维空间谱估计。
We can estimate two dimensional spatial spectra of sources in colour Guassian noises by eigen decomposing the matrix.
接着，论文对导出的原始图像直方图曲线进行分解，得到最接近直方图形状的高斯函数曲线。
Next, the estimated histogram is decomposed so as to get Gaussian curves nearest to the shape of the histogram.
本文还对奇异积分的高斯积分精度进行了计算分析，从量值上来反映高斯积分解决奇异积分的可靠性。
In the end, we calculate the precision of the gauss integral in dealing with singularity integral, which reflecting the reliability of this method.
重点分析了高斯金字塔、拉普拉斯金字塔、对比度金字塔和小波金字塔在图像分解与重构中的原理及其融合算法。
The principle of image decomposition and reconstruction based on Gauss-pyramid, Laplacian-pyramid, contrast-pyramid and wavelet-pyramid is emphatically analyzed, as well as the fusion algorithm.
为了避免经验模式分解(EMD)过程中不同时间尺度函数间的模式混叠，采用基于高斯白噪声加入的经验模式分解方法，并将之应用于旋转机械故障诊断中。
The EMD added Gauss white noise is proposed to avoid mode mixing of different time-scale IMF, and is applied in fault diagnosis for rotating machine.
为了避免经验模式分解(EMD)过程中不同时间尺度函数间的模式混叠，采用基于高斯白噪声加入的经验模式分解方法，并将之应用于旋转机械故障诊断中。
The EMD added Gauss white noise is proposed to avoid mode mixing of different time-scale IMF, and is applied in fault diagnosis for rotating machine.
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