Capon_output

基于matalab的信道自适应均衡技术研究(Matalab based channel adaptive equalization technology research)

对生成的随机序列进行自相关（平衡性）进行测试。(Autocorrelation test )

传统波束形成算法一般采用最小方差MVDR，本算法采用恒模算法，迭代得到最优解，附有文献可参考，性能很好( Conventional beamforming algorithms generally use the minimum variance MVDR, this algorithm CMA iterative optimal solution, with literature can refer, good performance)

《MATLAB时尚百例实例》实例1-13()

基于MatlabRTW的机器人伺服系统设计方案(MatlabRTW-based servo system of robot design)

智能天线 电子工业出版社 【美】 Frank Gross著 何业军 等译 (Smart Antenna Electronics Industry Press [United States] Frank Gross translation of what industry and military)

说明：  内点法的机组组合程序，采用不可行内点启动的原对偶线性规划内点法，采用了稀疏技术(unit commitment program using interior method)

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 " )

神经网络变量筛选—基于BP的神经网络变量筛选,MATLAB的经典算法(Neural network variable selection- based on BP neural network variable selection, MATLAB classical algorithm)

FFT变换及逆变换，用FFT进行简单滤波，自功率谱和互功率谱(FFT transform and inverse transform, a simple FFT filter, auto power spectrum and cross power spectrum )