3dcrack

可进行最小二乘法线性拟合输出，包含源代码及生成后的程序(Least-squares linear fit can be output)

汽车课设货车Matlab驱动力图程序，分析了该信号的时域、频域、倒谱，循环谱等,光纤陀螺输出误差的allan方差分析。( Car class-based truck driver trying to Matlab program, Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. allan FOG output error variance analysis.)

《遗传算法及其在电力系统中的应用》华中科技大学版("Genetic Algorithms and Their Applications in Power Systems" 2002)

二阶精度的FDTD正演算法，可用于井间电磁波探测模拟(The accuracy of the second order FDTD are algorithm Can be used to detect simulation between Wells electromagnetic waves )

gmres 方法。视图求解线性方程组A*x=b的解x。nXn的稀疏矩阵A必须是方程且应是大型稀疏矩阵。列向量b的长度必须为n。(gmres method. View solving linear equations A* x = b the solution x. nXn sparse matrix A must be equation and should be large sparse matrix. The length of the column vector b must be to n.)

自己实现的一个简单的计算器，支持大数的加减乘除、开平方等操作，不适用库函数。(Themselves to achieve a simple calculator, to support the addition and subtraction, multiplication and division of large numbers, such as square root operations, library functions do not apply.)

对比卡尔曼滤波和维纳滤波对一阶gaussian-markov过程的滤波预测。(Contrast Kalman filter and Wiener filter of first-order gaussian-markov forecast filtering process.)

计算多材料单元平均应力应变,用于提取计算等效弹性模量 泊松系数(Calculate the average stress-strain of multi-material elements)

动态CGE模型代码，可以直接粘贴至GAMS软件运行，代码清晰，易于修改。(Dynamic CGE model code, can be directly pasted to the GAMS software operation, the code clear, easy to modify.)

一般线性规划问题具有线性方程组的变量数大于方程个数，这时会有不定的解。当决策变量个数n和约束条件个数m较大时，单纯形法是求解线性规划问题的通用方法。 从线性方程组找出一个个的单纯形，每一个单纯形可以求得一组解，然后再判断该解使目标函数值是增大还是变小了，决定下一步选择的单纯形。通过优化迭代，直到目标函数实现最大或最小值(In general linear programming problems, the number of variables with linear equations is greater than the number of equations. When the number of decision variables n and constraint number m are large, simplex method is the general method for solving linear programming problems. Find out one by one from the linear equations of the simplex, each a simplex can get a set of solution, and then concludes that the solution is the objective function value increases or smaller and decided to choose the next simplex. By optimizing iteration, until the target function achieves the maximum or minimum value.)