Autocorrelation-Gold

wiener filter matlab源代码(wiener filter)

光伏逆变系统的最大功率点跟踪算法，采用的是扰动观察方法，采用s函数编写，可直接载入simulink使用(maximum power point tracking method using perturb and observe method, written by s-function)

小波方法应用到故障诊断，灰度值显示，具有很好的实用价值(Wavelet method is applied to fault diagnosis, gray value shows that have good practical value)

single layer perceptron algorithm

本程序主要通过仿真动态显示均匀平面电磁波中，磁场 Hz 的波阵面在自由空间（理想介质）中的传播。(The program primarily through dynamic simulation shows uniform plane wave, the magnetic field Hz wavefront in free space (ideal medium) in the transmission.)

在matlab中调用libsvm的时候数据归一与反归一 在matlab中调用libsvm的时候数据归一与反归一(in Matlab call libsvm time data normalization and anti-normalization in Matlab emphasized libsvm used when a data normalization and anti-normalization)

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 " )

MATLAB An Introduction with Applications, 4th Edition EBook helps to Know about MATLAB and its apllications.

慢特征分析 sfa matlb源程序 参考文献： Wiskott, L. and Sejnowski, T.J. (2002), "Slow Feature Analysis: Unsupervised Learning of Invariances",(Slow feature analysis SFA MATLB source program)

mRMR算法，用于特征选择，包含代码和例子(mRMRalgorithm for feature selection, code and example)