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high_order_cumulant
- 使用MATLAB完成高阶矩及高阶累积量的函数
EVM
- 该算法是经典的信噪比估计算法——误差矢量幅值法，通过计算接收信号中同相分量和正交分量的二、四阶矩，该算法能够很好的估计信号的信噪比-The algorithm is a classic signal to noise ratio estimation algorithm- the error vector magnitude method, by calculating the received signal with the phas
comGLCM
- 计算四个方向上的灰度共生矩阵以及角二阶矩，熵，对比度，均匀性-Calculate four directions on the GLCM, as well as angular second moment, entropy, contrast, uniformity
get_hos
- 获取图像的高阶统计量，这里采用的是四阶矩-Obtain images of higher-order statistics, here is the fourth-order moments using
MATLAB2
- 用matlab的四阶矩方法进行可靠度解析科学计算-Matlab fourth moment method for reliability resolve scientific computing
wuchashiliangfuzhifa
- 通过计算接收信号中同相分量和正交分量的二、四阶矩，该算法能够很好的估计信号的信噪比-By calculating the received signal with the phase and quadrature components of the two, the fourth moment, the algorithm can estimate the signal to noise ratio
6434esdfsdf
- 针对标准均值滤波存在的问题,提出自适应均值滤波算法。算法首先计算窗口的四阶累积量和二阶中心矩并确定噪声 点阈值 然后根据窗口内噪声点个数自适应调整滤波窗口,自适应计算权值 最后对噪声点逐点滤波。该方法既能有效去除图 像噪声点,又能较好保持图像细节。论文最后给出实验和分析,结果表明该方法是有效的-Standard mean filter exists, adaptive mean filtering algorithms. The
M2M4method-SNR-estimation
- 一种基于信号二阶四阶矩的信噪比估计方法，该文件中包含该方法的文章以及matlab程序。-This estimation method is based on the signal second-order signal-to-noise ratio of the fourth moment. The file contains a paper and a code.
ica
- 神经网络中用四阶矩法取图像的基，以及怎样把图像分成小块-Neural network using fourth-order moment method in image base, as well as how to put the image into small pieces
M2M4-SNR-estimination
- 经典的二阶矩四阶矩信噪比估计，有不经过上采样、成型滤波和经过上采样、成型滤波的两种版本。加噪方式也分别用了matlab自带函数和自写两种版本。望大家参考。-Second Moment classic SNR estimation fourth moment, there is not through the sampling, the shaping filter and sampled, two versions of shaping
r
- 可靠度计算中矩法较为常见，本程序应用四阶矩法以及改进四阶矩法计算可靠度。(the fourth order moment method calculate reliability)
25208810cyclic_cumulants_fast
- 计算信号的高阶矩以及四阶，六阶，八阶累积量(calculate High order cumulants of signals)
garchsk
- Jondeau 、Leon 等提出自回归条件方差—偏度—峰度模型(GARCHSK)，用于同时描述收益率二阶矩、三阶矩和四阶矩的时变特征。此文件为该模型代码。(Jondeau, Leon et al. Proposed an autoregressive conditional variance-skewness-kurtosis model (GARCHSK), which was used to describe the time-v