beam

分数傅里叶变换和分数余弦变换，动态展示实部，虚部和模值(Computation of the Fractional Fourier Transform)

有限元法计算程序，运用三角单元，进行线性插值，处理平面问题。(finite element method)

说明：  用四阶Runge-Kutta法解延迟微分方程组，用到的朋友看一下啊(Using fourth-order Runge-Kutta method for delay differential equations, a friend used to look at ah)

使用惩罚函数法对机械设计中的问题进行优化处理(The use of penalty function method for mechanical design optimization problems deal with)

计算fluent相变的udf模型，包括气相到液相，液相到气相的双向传递。(Calculate the udf model of fluent phase transition)

Gatheral SVI模型包含 raw SVI， Surface SVI 和含有跳过程的SVI(This is a document about the SVI model codes of J.Gatheral including raw SVI, Surface SVI and SVI with jump)

地球科学（Fortran90）: 计算空间重力异常、扰动重力、垂线偏差或重力梯度的垂向梯度。 计算方式：数值积分、二维平面FFT、二维球面FFT或一维FFT。(Earth Science (Fortran90): calculate the gravity anomaly, gravity disturbance, the deflection of the vertical or gravity gradient vertical gradient. Calculation: numerical integration, FFT of the two-dimensional plane, two-dimensional spherical FFT or one-dimensional FFT.)

vc++实现编译原理中的LL(1)文法的编译过程,非常好用.(vc realization of the principle of compiler LL (1) grammar compiler course, very handy.)

实现矿井采空区的孔隙率和粘性阻力系数，主要用于采空区瓦斯抽采(The porosity and viscosity resistance coefficient of mine goaf can be achieved.)

％ 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)