inpolygon.f

DFP法求优化问题的C++源代码，经测试，该程序运行正常，得到了预期的结果。(DFP method for the optimization of C++ source code, tested, the program works correctly to get the desired results.)

在通訊系統中常見到的cordic，是個用很少複雜度就能實現三角函數的電路，檔案中有C語言的CORDIC程式(In the communication system common to cordic, is a little complex to use trigonometric functions will be able to realize the circuit, the file has C language program CORDIC)

从旋转矩阵到四元数的转换，matlab代码。(From the rotation matrix to quaternion conversion, matlab code.)

用麦克麦考方法求解一维burgers方程的matlab代码(By Mike McCaw method for solving one-dimensional burgers equation matlab code)

利用matlab针对图像进行马氏距离计算 ,LDPC码的完整的编译码，线性调频脉冲压缩的Matlab程序。( Using matlab to calculate the Mahalanobis distance for the image, Complete codec LDPC code, LFM pulse compression of the Matlab program.)

该程序用于瞬变电磁勘探近区场计算，只要输入不同参数便可以得到近区场的视电阻率(The procedure transient electromagnetic exploration for near field calculations, as long as the input parameters can be different near field apparent resistivity)

模拟隧道开挖后受力及变形，初始地应力清零及接触面分析处理。( U6A21 u62DF u96A7 u9053 u5F00 u6316 u53D7 u53B0 u53E u53E u53F8 u53E U6790 u5904 u7406 u3002)

说明：  移动最小二乘法程序，用MATLAB编写的函数形式，直接可以调用(Moving Least Square Method)

有限单元法基本原理和数值方法,书籍，供学习参考(The basic principle of finite element method and numerical methods)

％ 奇异值分解 (sigular value decomposition,SVD) 是另一种正交矩阵分解法；SVD是最可靠的分解法， ％ 但是它比QR 分解法要花上近十倍的计算时间。[U,S,V]=svd(A)，其中U和V代表二个相互正交矩阵， ％ 而S代表一对角矩阵。 和QR分解法相同者， 原矩阵A不必为正方矩阵。 ％ 使用SVD分解法的用途是解最小平方误差法和数据压缩。用svd分解法解线性方程组，在Quke2中就用这个来计算图形信息，性能相当的好。在计算线性方程组时，一些不能分解的矩阵或者严重病态矩阵的线性方程都能很好的得到解( Singular value decomposition (sigular value decomposition, SVD) is another orthogonal matrix decomposition method SVD decomposition is the most reliable method, but it takes more than QR decomposition near ten times the computing time. [U, S, V] = svd (A), in which U and V on behalf of two mutually orthogonal matrix, and the S on behalf of a diagonal matrix. And QR decomposition are the same, the original matrix A is no need for the square matrix. The use of SVD decomposition method are used as a solution of least squares error method and data compression. Using SVD decomposition solution of linear equations, in Quke2 on to use this information to calculate the graphics performance quite good. In the calculation of linear equations, some indecomposable matrix or serious pathological matrix of linear equations can be a very good solution)