use-matlab-get-excel-information

PCA的步骤： 1 先将数据中心化； 2 求得的协方差矩阵； 3 求出协方差矩阵的特征值与特征向量； 4 将特征值与特征向量进行排序； 5 根据要降维的维数d’,求得要降维的投影方向； 6 求出降维后的数据； (PCA steps: 1 of the first data center 2 covariance matrix obtained 3 obtained covariance matrix eigenvalues and eigenvectors 4 eigenvalues and eigenvectors will be sorted 5 according to the dimension of dimension reduction d ' , seek to reduce the dimension projection direction 6, the data obtained after the dimensionality reduction )

利用matlab对随机过程课程的仿真 1、利用matlab绘制随机过程的谱密度G_x (ω)=2αβ/(β^2+ω^2 ) (α、β为正数)的图像。 2、绘制白噪声的功率谱密度函数G_x (ω)=N/2和自相关函数R_N (τ)=N/2 δ(τ)的图像。 3、分析低通白噪声和带通白噪声的功率谱密度函数和自相关函数的性质并举例同时绘制其图像。 (1, drawn using a random process matlab spectral density G_x (ω) = 2αβ/(β ^ 2+ ω ^ 2) (α, β positive) image. 2 for the white noise power spectral density function G_x (ω) = N/2 and the autocorrelation function R_N (τ) = N/2 δ (τ) of the image. 3, the analysis of low-pass white noise and band-pass white noise power spectral density function and autocorrelation function of the nature and the examples at the same time to draw its graphics.)

这是ofdm的毕设报告，里面有相应知识的学习最后还附加了ofdm的仿真，同时还有仿真图的分析(This is the complete set of ofdm report, which has the appropriate knowledge, learning and finally added ofdm simulation, as well as the analysis of simulation diagram)

autocov computes the autocovariance between two column vectors X and Y with same length N using the Fast Fourier Transform algorithm from 0 to N-2. The resulting autocovariance column vector acv is given by the formula: acv(p,1) = 1/(N-p) * sum_{i=1}^{N}(X_{i} - X_bar) * (Y_{i+p} - Y_bar) where X_bar and Y_bar are the mean estimates: X_bar = 1/N * sum_{i=1}^{N} X_{i} Y_bar = 1/N * sum_{i=1}^{N} Y_{i} It satisfies the following identities: 1. variance consistency: if acv = autocov(X,X), then acv(1,1) = var(X) 2. covariance consistence: if acv = autocov(X,Y), then acv(1,1) = cov(X,Y)

对经典协议LEACH的改进版本，可以出图3个，对初学很有帮助，大家有兴趣的可以看看。(LEACH agreement on an improved version of the classic, you can plot three, very helpful for beginners, we are interested can look at.)

研究生毕业论文中的一部分MATLAB源代码，实现压缩卡尔曼滤波算法，包含了仿真结果。(Graduate thesis part of the MATLAB source code, to achieve compression Kalman filter algorithm, including the simulation results.)

说明：  求地震动的加速度反应谱 速度谱 位移谱(Acceleration response spectrum for ground motion velocity spectrum displacement spectrum)

独立成分分析的matlab实现，适合初学者学习和使用(Independent component analysis matlab implementation, suitable for beginners to learn and use)

阵列天线的DOA估计MUSIIC算法，只有几行简单易懂的代码 (The array antenna DOA estimation MUSIIC algorithm, and only a few lines of easy-to-understand code)

matlab gui, 包括了4个很好的例子： 1.具有多个坐标轴的GUI，主要学习控制哪一个坐标轴是绘图命令的对象和用编辑文本框读入输入的数。 2.列表框目录阅读器，主要学习获取路径，加载，打开文件 3.从列表框中存取工作区变量，学习把存在于基本工作区的变量名放进列表框，选择多项等 4.地址簿阅读器，这个比较综合，用得技术也比较多。包括打开，保存，修改mat文件，利用handles结构保存和重新调用共享数据。(matlab gui, including four very good example: 1. with multiple axes of GUI, the main learning control which axis is the object of drawing commands and edit the text boxes with the number of read input. 2. The list box directory reader, the main study to obtain the path, load, open the file 3. From the variable list box to access the work area, learning the basic work area exists in the variable names into the list box, select a number of other 4 . address book readers, the more integrated, more technology used. Including open, save, modify mat file, save and re-use handles structure called shared data.)