jisuan

说明：  使用fortran编写的无网格（光滑质点流体动力学）SPH算法(using FORTRAN prepared by the non-grid (smooth particle hydrodynamics) SPH algorithm)

说明：  常用算法包括第一类整数阶贝塞耳函数，积分刚性方程组的吉尔方法，计算多重积分的高斯方法，快速傅利叶变换，离散随机线性系统的卡尔曼滤波，切比雪夫曲线拟合的c语言算法(failed to translate)

smote过采样方法对不平衡数据集进行人工数据合成(smote oversampling and classification)

用fortran语言编写的传统矩量法求解立方体的RCS的程序。(The fortran language prepared by the traditional method of moments for solving the cube RCS program.)

说明：  abaqus周期性边界条件代码，可以参考学习(ABAQUS periodic boundary condition code can refer to learning)

最小二乘法拟合进行n次多项式拟合，N用来控制拟合的次数，例如N=5时进行4次多项式拟合，还回的是拟合系数(Least squares fit polynomial n times, N is used to fit the number of control, e.g., N = 5 When quartic polynomial fitting, further back are fitting coefficients)

计算在不同湿度下，不同频率下，大气的衰减系数。(Calculation under different humidity, different frequencies, atmospheric attenuation coefficient.)

The following is an example of how Microsoft Solver Foundation can be used to solve a constraint satisfaction problem (CSP) like generating a typical Sudoku problem. Sudoku http://www.codeproject.com/Articles/419389/Sudoku-using-Microsoft-solver-foundation In this article I do not attempt to explain everything there is to know about constraint satisfaction problems, but I will go over the concepts in the hope that even if you have never heard of CSP you will still get the idea.

电容层析成像的ART算法演示实例,并带有详细的说明(An Example of ART Algorithm for Electrical Capacitance Tomography)

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.)