Bessel_Transforms

计算方法程序:多项式拟合(Calculation procedure: Polynomial Fitting)

用切比雪夫多项式逼近已知函数 用勒让德多项式逼近已知函数 用帕德形式的有理分式逼近已知函数 用列梅兹算法确定函数的最佳一致逼近多项式 求已知函数的最佳平方逼近多项式 用傅立叶级数逼近已知的连续周期函数 离散周期数据点的傅立叶逼近 用自适应分段线性法逼近已知函数 用自适应样条逼近（第一类）已知函数 离散试验数据点的多项式曲线拟合 离散试验数据点的线性最小二乘拟合 离散试验数据点的正交多项式最小二乘拟合 (By using Chebyshev polynomial approximation of the known functionApproximation of the known functions by Legendre polynomialsApproximation by rational fraction of known function in the form of PadmaTo determine the best uniform function polynomial approximation with the Lemez algorithmThe best known polynomial square for function approximationContinuous periodic function with Fourier series approximation of the knownApproximation of discrete data points in the Fu Liye cycleApproximation of the known function with adaptive piecewise linear methodAdaptive spline approximation ( first class ) known functionPolynomial curve fitting of discrete data pointsLinear least squares fitting of discrete data pointsOrthogonal polynomial least squares fitting of discrete data points)

用有限差分方法求解波动方程，画出波场快照，模拟波在地下传播！(The wave equation by finite difference method, draw the wave field snapshot, simulate wave propagation in the underground!)

Code for Classification of points

完成了复数矩阵的计算,采用了并行算法原理，较快速的处理了稀疏矩阵方程结构。(Completed a complex matrix computation, parallel algorithm principle, more rapid processing of the sparse matrix equation structure.)

umat subroutin for 2d ladovez damage model i ncomposite materials

homagrapy matrix to find the homagrapy matrix from two pictures, first you need to get a set of coorlation vector

最小二乘法和总体最小二乘法，来自《矩阵分析与应用》(Least squares and total least squares method the Matrix Analysis and Applications )

使用ABAQUS软件进行过渡网格划分，帮助用户建立良好的过渡网格的小工具(use the ABAQUS to divide the transition gridding)

利用FFT估计正弦信号的频率,要估计一个叠加了高斯白噪声的正弦信号 的频率 ，可以通过对x(n)做傅里叶变换，得到频谱图，找出幅度的最大值对应的频率值 ，进行多次变换，求出均方误差 。改变信噪比SNR，通过仿真可以得出随着信噪比增加，均方误差减小。(Sinusoidal signal using FFT frequency estimation, to estimate a Gaussian white noise superimposed on the frequency of sinusoidal signals, can be achieved by x (n) be the Fourier transform to get spectrum to identify the magnitude of the frequency value corresponding to the maximum , several transformations, find the mean square error. Change the signal to noise ratio SNR, the simulation can be drawn as the SNR increases, the mean square error decreases.)