用Ｃ＃制作的一个简单程序，具体实现具体如下：将文本框中的数据保存为＊.txt文件，并实现再次读取功能...

基于matlab的手势识别代码，有gui编写界面(Gesture recognition code based on matlab, GUI programming interface)

OMAP5912 UART的测试程序 包括头文件 源文件等。(OMAP5912 UART program test)

说明：  TMS320F28335 的中断程序,该程序是基于CPU中断的程序；程序已经完成编译并能够在板子上跑通；(Interrupt process by TMS320F28335)

字符串截取/图片地址提取/ip地址检测。。。。

采用MFC特有的VFW类实现对电脑摄像头和USB摄像头信息的读取

网格点代码是一个从地理坐标中生成代码，用来作为邮政编码来定位一个位置的库。(Grid Point Code is a Library to generate code from Geographical Coordinates to be used as Postal Code to pinpoint a location)

基于MFC的TCP/IP socket编程，一个客户端程序，适合初学者学习，开发平台vs2015(TCP/IP SOCKRT programing based on MFC,A client program ,very good for first learner the develop platform is vs2015)

利用matlab的gui设计的带有输入和输出功能的界面图形，实现等距线可视性很强，自己独立编写的数据和图形，学习非常值得(Using GUI of MATLAB to design interface graphics with input and output functions, realizing the visibility of isometric line is very strong, the data and graphics written independently by oneself are very worthwhile to learn.)

程序名为LU分解法。功能：求解系数矩阵为非奇异的线性代数方程组Ax=b，它能串联式地逐次解A相同b不同的方程组。本方法将高斯主元消去法中的中间结果的记录次数从约n^3/3次减少到约n^2次。子过程LUDCMP将系数矩阵A分解为上三角矩阵和下三角矩阵。子过程LUBKSB利用LUDCMP的分解结果求得线性方程组Ax=b的解。(Program called LU decomposition. Function: non-singular coefficient matrix solving linear algebraic equations Ax = b, it tandem to the same b successive solution A different equations. The method of the Gaussian elimination method master record of the results of the intermediate frequency from about n ^ 3/3 was reduced to about n ^ 2 times. Sub-process LUDCMP the coefficient matrix A is decomposed into upper triangular matrix and lower triangular matrices. Sub-process LUBKSB decomposition results obtained using the LUDCMP linear equations Ax = b solution.)

用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)