DOA

Generalized Method of Moments(GMM) 广义矩方法，是用来估计模型参数的计量经济学过程。具体说明见其中的gmmdoc.pdf。(Generalized Method of Moments (GMM) GMM method is used to estimate model parameters Econometrics process. See which specify gmmdoc.pdf.)

一個把HHT程序用matlab實踐的檔 HHT Process(HHT Process)

matlab 上进行滤波器设计一个很好的例子(how to design filter )

说明：  这是一个rs编码程序，希望能帮到大家，可以查漏补缺。(This is a rs coding procedures, I hope to help you, can leak filled.)

说明：  用MATLAB编写的求曲线拟合的程序，希望大家分享一下。我是新来的。(Prepared using MATLAB for curve fitting process, I hope to share with Members. I was new.)

绝对的lowe老人家提出的sift算法源码，配套有文档说明，对于初学者极度有用，还有我添加的注释我移植的仿射变换函数，绝对值得下的资源~！(The absolute lowe elderly sift algorithm proposed source code, supporting have documented for beginners extremely useful, and I add comments I transplanted affine transformation function, absolute worthy resource ~!)

说明：  利用FIR滤波器设计一个低通滤波器，能够分析到电力系统中的三次谐波，要求满足如下指标：截止频率150HZ，阻带衰减≥30db(FIR filter design using a low-pass filter, to analyze the power system in the third harmonic, the requirements to meet the following indicators: cut-off frequency 150HZ, stopband attenuation ≥ 30db)

本代码是CLARK和PARK变换的m文件和simulink模型，即从三相坐标变换到两相坐标的变换。(This code is CLARK and the PARK transform of the m file and the Simulink model, namely from the three-phase to two-phase coordinate transformation of coordinate transformation.)

This is about source code management.

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 " )