svdsim

数学交互界面，可以实现求解线性方程组，三维绘图，二重积分等(Math interactive interface for solving linear equations, three-dimensional drawing, the double integral)

program simulates the electrostatic precipitator behaviours, developed in simulink toolbox of matlab.

正六边形边界条件下的热扩散（自由扩散）的模拟(regular hexagen B.C. )

流水线ADC信噪比测试程序,最后一级flash位数可调，可进行SNDR和SFDR的测试(SNDR test for pipelined ADC)

最小二乘法是一种数学优化技术。它通过最小化误差的平方和寻找数据的最佳函数匹配。利用最小二乘法可以简便地求得未知的数据，并使得这些求得的数据与实际数据之间误差的平方和为最小。最小二乘法还可用于曲线拟合。其他一些优化问题也可通过最小化能量或最大化熵用最小二乘法来表达。(Least squares method is a mathematical optimization techniques. It matches by squaring and finding data to minimize the error of the best functions. Least square method can easily be obtained unknown data, and so these squared error between the obtained data and the actual data and the minimum. The least squares method can be used for curve fitting. Some other optimization problems can be expressed by the least squares method by minimizing or maximizing entropy energy.)

针对33节点编写的潮流程序,运用前推回代法，实用性很强(Flow program written for 33 nodes, use push backward substitution method very practical)

ofdm channel estimation using ls and mmse methode matlab code

认知无线电下中继传输场景，DF与AF在判决条件下进行转换(wireless nerwork based on relay with transformation between AF and DF in cognitive radio)

采用matlab编程，实现克里金差值算法(Using matlab programming, the difference between the kriging algorithm)

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.)