GSMK

特徵粹取（feature extraction）是特徵選取（feature selection）的延伸，簡單地說，我們希望將資料群由高維度的空間中投影到低維度的空間，因此，我們必須找出一組基底向量（base）來進行線性座標轉換，使得轉換後的座標，能夠符合某一些特性。 我們可以將特徵粹取分成「包含類別資訊」和「不包含類別資訊」兩大類。包含類別資訊指的是我們已經知道哪些資料分別歸屬於哪一類；而不包含類別資訊的特徵粹取則適用於我們不知道手上的資料點分別該歸屬於哪一類，甚至連該劃分成幾類都不知道的情況。對於這兩大類資料，可以分述如下： 對於「不包含類別資訊」的資料，我們通常使用「主要分量分析」（principal component analysis），簡稱 PCA。 (Cuiqu features (feature extraction) is feature selection (feature selection) extension, simply put, we want to base the projection data the high-dimensional space to low-dimensional space, so we have to find a set of basis vectors ( base) to the linear coordinate conversion, so that after the coordinate conversion, can meet a number of features. We can feature Cuiqu into " category contains information" and " does not contain a category of information," two categories. Contains categories of information refers to what we already know what kind of information are attributed to Cuiqu features include categories of information are not applicable to information we do not know the points are in the hands of the home in which category, and even that is divided into several class do not know the situation. For these two categories of information, can be divided as follows: For information " does not include the categories of information" , we usually use the " )

采用极大值法实现图像处理中的小波去模糊。基于matlab函数实现。(Using the maximum value method to achieve image processing wavelet deblurring. Based on matlab function implementation.)

改进欧氏距离测度算法，可以比较特征向量的距离相似度(Improved algorithm Euclidean distance measure, you can compare the similarity distance of feature vectors)

由方波代替了SPWM，实现了SPWM电机调速(Replaced by a square-wave SPWM, motor speed to achieve the SPWM)

对学习阵列信号有很大的帮助，对初学者很实用！(In learning array signals are of great help for beginners very useful)

说明：  非常著名的爱尔朗公式的实现,主要对排队思想的进一步编程实现(Well-known Erlang formula to achieve, mainly on the line thinking further programming)

A very simple code to help you to calculate the aritmetic average on the IDL interface.Works in all the IDL versions

Shooting algorithm implemented in Matlab for solving the Lasso [1] and group Lasso [2] problems in the penalized form.

这是matlab的图像处理学习文件，自己花钱买来的资料，不是网上随便下载的。(This is a learning matlab image processing files, their own money to buy the information, not just downloaded online.)

matlab中的JC法例程。可应用与可靠度计算等工程实例中。(JC method in matlab routine. Examples of application and reliability engineering can be calculated and the like.)