extr

说明：  在Matlab中模拟“落体偏东”想象。物理上，非惯性系下相对运动会产生科里奥利力，正是在科氏力下，地球上的运动物体才会产生偏转。(Simulated in Matlab, &quot off the body towards the east&quot Imagine. Physically, non-inertial Coriolis force generated in the relatively Games, is in the Coriolis force, the earth will produce deflection of moving objects.)

MATLAB教程，很不错的英文版教程。讲解比较全面细致，介绍由浅入深，容易学习。(MATLAB Tutorial, very good English tutorial. More comprehensive and detailed explanation, description Deep and easy to learn.)

Genetic and matlab programming

一个小波边缘检测的MATLAB程序,一个小波边缘检测的MATLAB程序(One of the MATLAB wavelet edge detection procedure, one of the MATLAB wavelet edge detection procedure)

用matlab求图像阈值分析程序，一种是直方图阈值法一种是最大类间方差(Using matlab and image threshold analysis program, a variance between a Histogram method is the largest class)

MATLAB 退火法，元胞机等程序书写与应用及实例。(MATLAB program)

通过本试验，基本掌握FFT算法的实现原理，同时能利用MATLAB语言编写完成FFT算法，并对给定的信号进行频谱分析。实验设备：通用计算机＋MATLAB 6.0软件。 (Through this test, basically mastered the FFT algorithm implementation principle, while able to use MATLAB language to complete FFT algorithm, and a given signal spectrum analysis. Experimental equipment: general-purpose computer+ MATLAB 6.0 software.)

说明：  matlab程序读取EXCELL格式的数据，感觉好的话，就顶一下，程序可用(matlab program to read Excel data format, I feel good, look on the roof, procedures available)

ANALYSIS OF D-FLIPFLOPS

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.)