Image-Statistics

用互信息作为两幅图像的相似性度量进行配准(Using mutual information as the two images of the similarity measure for registration)

说明：  C++的简单例子，让你对C++有个基本的了解。(A simple example of C++, C++ so you have a basic understanding.)

MSK调制算法，包括了附加相位的算法和一系列的波形图(MSK modulation algorithm, including an additional phase of the algorithm)

此文档是我做APF时参考过的无数文章中最有价值的文档之一，写的很深刻，也很结合实际。(This document is one document that I do APF reference to numerous articles in the most valuable, written in a very profound and very actual.)

基于负熵的盲源分离源程序,对盲源分离领域属于最基本的程序(BSS based on negentropy)

用Matlab对随机语音信号进行处理，编制基于GUI格式的随机信号处理工程(Using Matlab to random voice signal processing system based on GUI format, the random signal processing engineering )

计算有空气孔介质光子晶体的色散曲线，供大家交流，互相学习(Calculated free pore Photonic crystal dispersion curves for all to exchange, learn from each other)

说明：  利用传输矩阵法计算光纤啁啾brag光纤光栅滤波器的温度滤波特性(The use of transfer matrix method to calculate fiber chirped fiber Bragg grating filter brag temperature filtering properties)

Relief算法中特征和类别的相关性是基于特征对近距离样本的区分能力。算法从训练集D中选择一个样本R，然后从和R同类的样本中寻找最近邻样本H，称为Near Hit，从和R不同类的样本中寻找最近样本M，称为Near Miss，根据以下规则更新每个特征的权重： 如果R和Near Hit在某个特征上的距离小于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻是有益的，则增加该特征的权重；反之，如果R和Near Hit在某个特征上的距离大于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻起负面作用，则降低该特征的权重。(The correlation between feature and category in Relief algorithm is based on distinguishing ability of feature to close sample. The algorithm selects a sample R from the training set D, and then searches for the nearest neighbor sample H from the samples of the same R, called Near Hit, and searches for the nearest sample M from the sample of the R dissimilar, called the Near Miss, and updates the weight of each feature according to the following rules: If the distance between R and Near Hit on a certain feature is less than the distance between R and Near Miss, it shows that the feature is beneficial to the nearest neighbor of the same kind and dissimilar, and increases the weight of the feature; conversely, if the distance between R and Near Hit is greater than the distance on R and Near Miss, the feature is the same. The negative effect of nearest neighbor between class and different kind reduces the weight of the feature.)

kalman滤波算法程序是matlab的程序(An improved adaptive filter state estimation, the effect is definitely a good thing, is to use MATLAB prepared directly in matlab run will be able to see the effect of a perfect filter, adaptive algorithm is sage-husa algorithm, a more traditional filter machine has greatly improved)