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研究阵列的信号经典算法，MUSIC，已经测试过了，不错(Classical algorithm of the signal array, MUSIC, has been tested, and good)

一个新设计的OTSU算法，使用方法如下：％ load clown ％ subplot(221) ％ imshow(X/max(X(:))) ％ title( Original , FontWeight , bold ) ％ for n = 2:4 ％ Iseg = otsu(X,n) ％ subplot(2,2,n), colormap(gray) ％ imshow(Iseg) ％ title([ n = int2str(n)], FontWeight , bold ) ％ end(OTSU design a new algorithm, using the method as follows: load clown subplot (221) imshow (X/max (X (:))) title (Original, FontWeight, bold) for n = 2:4 Iseg = otsu (X, n) subplot (2,2, n), colormap (gray) imshow (Iseg) title ([n = int2str (n)], FontWeight, bold) end)

bioinformatics s function pseudo inv-robot

Band Pass Filter matlab command

使用随机方法计算Frobenius模并比较多种逼近方式的误差大小。(Calculating Frobenius norm using random method.)

Same functionality as the MATLAB rref function

科斯塔斯环载波恢复，用来跟踪输入信号的载波频率(carrier recovery by costas loop)

说明：  ransac算法Matlab 实现 RANSAC算法全称是随机抽样一致算法（random sample consensus,RANSAC），RANSAC算法的基本假设是样本中包含正确数据(inliers，可以被模型描述的数据)，也包含异常数据(outliers，偏离正常范围很远、无法适应数学模型的数据)，即数据集中含有噪声。(The ransac algorithm Matlab achieves the RANSAC algorithm's full name is the random sample consensus (RANSAC). The basic assumption of the RANSAC algorithm is that the sample contains the correct data (inliers, data that can be described by the model) as well as outliers (outliers). The normal range is too far to fit into the data of the mathematical model. That is, the dataset contains noise.)

1、NeuralNetwork_RBF_Classification.m - 分类 2、NeuralNetwork_RBF_Regression.m - 回归">

说明：  创建一个复数类，定义属性：实部、虚部。定义方法：复数加法、复数减法、复数乘法、求实部，求虚部，将复数输出，判断两个复数相等。通过一个类举例验证这些方法(Create a complex number class, custom attributes: the real part, imaginary part. Definition method: complex addition, complex subtraction, multiplication, complex, realistic Department, seeking the imaginary part, the complex output, determine the two complex numbers are equal. Verified through a class example of these methods)