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圆周卷积滤波器，可清晰见到实际滤波器的算法(Circular convolution filter, can clearly see that the actual filter algorithm)

有限元法计算平板受集中载荷的程序，二维四边形网格(finite element method concentrated load plate by the procedure, two-dimensional rectangular grid)

计算水声传播的快速场程序，使用了有限元方法，计算速度快，精度高。(underwater acoustic propagation Fast Field Program, using Finte Element Method,fast and accurate.)

ivf Fortran 有限元计算 一端固支 另一端自由移动的二维梁结构的振动(calculate the 2D beam vibration based on Finite Element Method in Fortran)

重力异常正演代码，请好好使用它。帮助学习。。。。(Gravity anomaly forward code, please use it well. Help learn)

基于D2Q9模型的LBM程序，用于计算方腔驱动流，对应何亚玲《格子Boltzmann方法的理论及应用》一书的源码(LBM D2Q9 model-based program used to calculate the square cavity driven flow, which corresponds He Yaling " Lattice Boltzmann Method Theory and Applications," a source book)

一维黎曼问题，计算流体力学，C和Frotran预言代码(Riemann problem)

说明：   这是几个常用的测试函数，通过这个测试函数可以比较算法性能的优劣。(This is a test of several commonly used functions, through this test function can compare the algorithm performance is good or bad.)

计算机算法设计与分析(第3版)课后答案-王晓东版_打印版,整本书的课后习题答案，包括算法实现题也有。(The also Computer Algorithm Design and Analysis (3rd Edition) afterschool Answer- Wang Xiaodong _ print edition, the book Homework answer, including algorithms title.)

共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(Conjugate gradient method (Conjugate Gradient) is between the steepest descent method between the method and Newton' s method, it takes only a first derivative information, but to overcome the steepest descent method convergence slow shortcomings, but also to avoid the Newton method needs to be stored Hesse and disadvantages of computing inverse matrix and the conjugate gradient method is not only one of the most useful methods to solve large linear equations, solution of large-scale nonlinear optimization is one of the most effective algorithm. In various optimization algorithm, conjugate gradient method is a very important one. The advantage is that a small amount of memory required, with step convergence, high stability, and does not require any external parameters.)