gaussian distribution中文是什么意思

• 高氏分布
• 高斯分布(曲线), 正态分布
• 高斯分布/正态分布
• 高斯分配
• 正态分布

• gaussian    adj. 高斯的。
• distribution    n. 1.分配，分发，配给；分配装置[系统]；配给品；配 ...
• bivariate gaussian distribution    二元高斯分布
• clipped gaussian distribution    截尾高斯分布
• complex gaussian distribution    复高斯分布
• gaussian distribution curve    高斯粒度分布曲线
• gaussian distribution formula    高斯分布公式
• gaussian distribution function    高斯分布函数
• gaussian distribution law    高斯分布定律; 正态分布定律
• gaussian distribution profile    高斯掺杂分布
• gaussian distribution table    正态分布表
• gaussian permeability distribution    高斯渗透率分布
• gaussian probability distribution    高斯概率分布
• inverse gaussian distribution    逆高斯分布
• non-gaussian distribution    非高斯分布
• normal gaussian distribution function    正态高斯分布函数
• asymptotically gaussian    渐近高斯性的
• filter, gaussian    高斯滤波器
• gaussglocke gaussian    高斯
• gaussian algorithm    高斯消去法
• gaussian approximation    高斯近似法
• gaussian beam    高斯光束; 高斯射束
• gaussian blur    高斯模糊，多参数可选，好
• gaussian chain    高斯链
• gaussian channel    高斯信道

• At last distribution functions of load modes in life service are presented . based on the resisting force model and load model , the limit state equations of rc bridge are formulated . according to the resisting force is time - dependent and vehicle load is the non - gaussian distribution , jc method is applied to calculate the time - dependent reliability index of rc bridge
  在抗力衰减模型及桥梁荷载模型的基础上，将可靠度理论引入桥梁结构的评定中，推导出了桥梁结构耐久性极限状态方程，并根据耐久性极限状态方程中抗力是时间的函数，以及车辆荷载为非正态分布的特点，应用当量正态法( jc法)编制相应的程序计算桥梁构件的时变可靠度指标。
• The intracavity photon density and initial population inversion density are assumed to be gaussian distributions instead of plan wave assumption , based on this assumption , the rate equations of diode - pumped intracavity - frequency - doubled passively q - switched laser are modified . through solving these space - dependent rate equations numerically , the results under different assumption are compared . 5
  将腔内光子密度和初始反转粒子数的平面波近似修正为高斯分布近似，独立地导出描述二极管泵浦内腔倍频-被动调q激光器的速率方程，并通过数值求解该方程比较了两种近似下脉冲特性的不同； 5 .实验验证了2中提出的实验方案，并对实验结果进行了分析。
• In this thesis , firstly , we introduce generalized gaussian distributions to model the distributions of dct coefficients of an el frame . then , according to quantization theory , we analyze the distortion - rate function of the generalized gaussian model , with which we conclude that for the actual fgs coding , the derivative of actual distortion - rate function usually decreases continuously as the rate increases , and then begins to increase slowly at a comparatively high bit rate . finally , guided by the
  然后分析了fgs编码的量化模式,并把它应用到ggd分布上,得到了ggd分布率失真函数的变化规律,从而获得实际fgs编码的率失真函数的变化规律,即fgs编码失真速率函数的导数先随着码率的增加而逐渐减小,然后在码率比较高的时候开始随码率的增加而缓慢地增加。
• Abstract : a improved method using simple instrument to expand gaussian distribution light field and get large - range homogeneous ideal light field was presented . an optical setup used to expand gaussian distribution light field was designed to improve the utilization ratio of light energy and satisfactory experimental results ware obtained
  文摘:提出采用简单器件，将高斯分布光场经再扩展，获得大范围均匀的理想光场的方法；设计了对高斯分布光场再扩展光路，并提高散射光场光能的利用率，取得良好的实验效果。
• The main idea of the combining watermarking is that the watermarking information is embedded into the high frequency section and the low frequency section of the wavelet domain respectively . we will embed a small logo watermarking using image fusion technology in low frequency and a gaussian distribution sequence with mean 0 and variance 1 in high frequency section by using of spread spectrum technology , so we can achieve a more robust watermarking
  复合水印嵌入技术的主要思想是在图像小波域的高频部分和低频部分分别嵌入不同的水印信息，在高频部分使用图像融合技术来嵌入一小的徽标水印，低频部分使用扩频技术嵌入一高斯分布序列，这样可以使水印的稳健性更好。
• After reviewing some statistical models proposed to better characterize the host signal in dct , dwt and spatial domain , we describe the statistical property of host signal using gaussian scale mixture distribution , which is more general and flexible . we also present a new method for estimating the parameters of generalized gaussian distribution rapidly
  研究了细节分量的统计模型，包括平稳高斯模型、平稳拉普拉斯模型、平稳广义高斯模型、局部平稳的高斯模型和高斯尺度混合模型，提出了一种广义高斯模型中形状参数的快速估计方法。
• By posing the difference on mathematical models between blind detection and non - blind detection , we devise the sign correlation detector ( scd ) and the normalized liner correlation detector ( nlcd ) based on the laplacian distribution model and the local gaussian distribution model of the host signal respectively . a series of experiments in dct domain and dwt domain show that these two detectors are more robust than linear correlation detector ( lcd )
  基于局部最优检测理论得到了广义高斯分布模型下盲检测器的一般形式?幅度一符号相关检测器，通过计算幅度一符号相关检测器相对于线性相关检测器的渐进相对效率，建立了渐进相对效率与宿主信号形状参数之间的关系，从理论上证实了幅度一符号相关检测器的高效性。
• Applying generalized gaussian distribution to statistical model of the alternating current coefficient of discrete cosine transform , an adaptive blind watermark detection algorithm is presented on the basis of sign detector and linear correlate detector and its probability efficiency is deduced
  摘要根据数字图像离散余弦变换域交流系数的广义高斯分布模型，在符号检测器和线性相关检测器的基础上，提出一种盲水印自调节的检测算法，并推导出该检测器有较高的检测效率。
• The main contributions of this thesis are as follows : generalized gaussian distribution ( ggd ) is a nice model for the dct coefficients and wavelet coefficients in theory and practice . with information and quantization theory , we mathematically prove that the derivative of ggd distortion - rate function exists and is not related to the variance of the distribution
  本文通过信息论和量化理论的知识,分析了广义高斯分布ggd率失真函数的基本属性,数学上严格证明了:以峰值信噪比psnr ( peaksignalnoiseratio )或信噪比snr为失真标准,广义高斯分布ggd的失真速率函数( distortion - ratefunction )的导数存在,并且与分布的方差无关。
• In former stl instruments , a laser beam with a gaussian distributed intensity was commonly used as the excitation source . nevertheless , the output of a high power laser is usually a superposition of multi - modes rather than a gaussian distribution ( tem00 ) . therefore , it is very convenient to add an aperture to get a top - hat beam
  以前的表面热透镜装置中,多使用高斯光束作为激励光,但由于高功率激光器一般为多模输出,要获得严格的基模高斯光束比较困难,而平顶光束可以通过在激光器前加一定大小的光阑实现,降低了对激光光束质量的要求,更有利于实际的测量。

• gaussian distributionとは意味：ガウス分布｛ぶんぷ｝