拉普拉斯分布

当误差服从拉普拉斯分布、柯西分布、污染正态分布时，稳健估计方法要显著优于OLS。

When the errors follow Laplace , Cauchy , contaminated normal distribu-tions , the robust estimation methods are significantly better than OLS .

非对称拉普拉斯分布在股票收益率中的应用

The Application of Asymmetric Laplace Distribution in Stock Returns

基于拉普拉斯分布模型的DCT域图像水印视觉可见性评估

Evaluating the Visibility of Image Watermarking in the DCT Domain Based on Laplacian Model

相较于拉普拉斯分布模型，图像经DCT变换后交流系数的分布更加符合柯西分布。

Compared to the Laplacian distribution model , the distribution of DCT transform coefficients is more in line with the Cauchy distribution .

为提高编码效率，通过分析残差系数在空域和DCT域均符合拉普拉斯分布后，提出一种快速DCT算法。

To improve encoding efficiency , by analyzing the distribution of residual coefficients in spatial-domain and DCT-do-main , the coefficients accord with a Laplacian distribution with zero mean .

该算法基于序列分析与突变检测的理论，考虑图像DCT系数满足拉普拉斯分布，给出了理想平稳拉普拉斯分布信号扩展频谱隐藏密钥估计的模型。

Considering the Laplacian distribution of image DCT coefficients , a secret key estimation model of stationary laplacian host signal embedded by spread spectrum steganography is presented based on the theory of detection of abrupt changes and sequential detection .

根据DCT交流系数的拉普拉斯分布模型，推导了DCT域典型水印算法中拉伸系数与信噪比和峰值信噪比之间的理论关系。

Based on the Laplacian distribution model of AC DCT coefficients , we deduce theoretical relationship between the scaling parameter in a typical watermarking algorithms and signal to noise ratio ( SNR ) or peak signal to noise ratio ( PSNR ) of watermarked images .

拉普拉斯分布顺序统计量的分布性质

On distributional properties of order statistics with Laplace distribution

由拉普拉斯分布概率密度函数推导得出的符号函数作为语音信号分离算法中的激活函数，目前广泛应用在基于独立分量分析的语音分离算法之中。

Speech separation algorithms using sign function deduced by Laplace distribution function as the activation function is used universal .

并在此基础上进行分析，从而用计算机模拟出了四种噪声信道中对应高斯分布和拉普拉斯分布的离散信号信息传输量。

On this basis , transinformations for discrete signals of Gauss and Laplace distribution in channels with four noise patterns are simulated .

话音信号的振幅分布特性服从拉普拉斯分布或伽玛分布，并与方差有关。

The amplitude distribution of speech signal keeps to the Laplacian distribution or Gamma distribution , and it is related to its variance .

一些统计模型，如超高斯模型如伽玛分布、拉普拉斯分布以及广义超高斯分布已被证明要优于高斯模型。

Some models such as the Gamma distribution , and Laplace distribution and the generalized super-Gaussian distribution have been proved to be better than Rayleigh model .

由于小波分解后的系数经活动性预测分类后具有拉普拉斯分布的性质，因此可对其采用预测分类的自适应量化方法进行编码。

Because coefficients match Laplacian distribution after classification based on their acitivity prediction , a context based classification and adaptive quantizer ( CBCAQ ) is used to them .

本文构造了n维P-范分布的密度函数，使拉普拉斯分布、正态分布、均匀分布与退化分布均为一维P-范分布的特例。

In this paper , the density function of n-dimensional P-norm distribution is derived . Laplace , Normal , Rectangular and Degenerate ones are the specific case of one-dimensional P-norm distribution .

首先，通过分析乐音信号的时频统计特性，假定乐音信号符合超高斯分布，且类似于拉普拉斯分布。

Firstly , by analyzing the statistical distribution characteristics of music signals in time and frequency domains , it is assumed that music signal is super-Gaussian distributed and is similar to Laplace distribution .

研究了小波子带图像系数的统计分布，发现小波子带图像系数分布和拉普拉斯分布非常相似，继而提出了一种基于其统计特征的图像量化编码算法。

We have studied the statistical distribution of wavelet subimage coefficients and concluded that the distribution of wavelet subimage coefficients is very much similar to that of Laplacian distribution . Based on the statistical properties of image wavelet decomposition , an image quantization algorithm is proposed .

研究表明，自然图像在局部邻域内具有很强的相关性，其相邻像素差分中零值的出现频次最多，可以近似用拉普拉斯分布对像素差分分布进行统计建模。

As is indicated in the former researches , natural images are highly correlated in a local neighborhood , the value zero appears most frequently in intensity differences between adjacent pixels , and the statistical model of the distribution of pixel difference can be established using the Laplace distribution .

信号的小波系数表现出很强的非高斯统计特性，其密度函数可以用推广的拉普拉斯先验分布建模。

The wavelet coefficients of signals have highly non-Gaussian statistics that may be modeled with generalized Laplacian distributions .

图像的小波系数具有很强的非高斯统计特性，可以建立推广的拉普拉斯先验分布，用贝叶斯估计对图像小波系数滤波来达到降噪目的。

The wavelet subband coefficients of images have highly non Gaussian statistics that may be modeled with generalized Laplacian distributions , and Bayesian estimation is used to suppress noise .

此外，本文还提出一种基于拉普拉斯先验分布的鲁棒回声状态网络模型。通过引入对异常点不敏感的拉普拉斯分布作为模型输出的先验，预测模型的鲁棒性得以提高。

Moreover , based on Laplace distribution , this paper proposes a robust ESN as well . By introducing Laplace distribution , which is robust to outliers , as the likelihood function of model output , the robustness of the prediction model can be enhanced .

基于拉普拉斯正态混合分布概率密度函数估计的语音分离算法

Speech separation algorithm based on Laplace normal mixture distribution probability density function estimation