Osculating

粘弹性人工边界的实现，在abaqus中快速施加粘弹性人工边界(Realization of viscoelastic artificial boundary, imposed by rapid visco-elastic artificial boundary in abaqus)

说明：  设计一个函数，其功能是同时求得长度为20的整型数组所有元素中的最大值、最小值和平均值。并用相应的主函数对其进行测试，测试数组可以用随机数填充或者自行定义数据。(The design of a function, its function is to obtain the length of the maximum, minimum and average 20 integer array element. And its main function testing, the test array can be populated with a random number or define your own data.)

得到一个人二值矩阵后，计算一个二值矩阵的聚类系数，来表示矩阵的特征(when you have a 0-1 matrix ,you can calculate its clusterig through my program)

应用于高速碰撞的相关子程序，考虑了在高速碰撞中单元畸变的沙漏模型。。(Related subroutines used in high-speed collision, taking into account distortion in high speed crash in the hourglass model unit. .)

FFT快速傅里叶变换，用于数字信号处理，大大提高了运行速度，节省内存开销。C语言实现(FFT fast Fourier transform for digital signal processing, greatly improving the speed and save memory overhead. C language)

说明：  Analysis of 2D structure using Mesh Free Method...

用于求解超定方程组最小二乘解，稳定性高，速度快(To get the least square solution of superlattice dislocation.)

采用贝叶斯推论的数据融合，将CHAN算法和泰勒算法的结结果经过处理，得到更好的定位结果，已通过测试。 (Bayesian inference using the data fusion, will CHAN Taylor algorithm and the results of algorrithm processed and better positioning of the results of the full source code, has been tested. )

计算岩石表面裂隙宽度并求取其表面粗糙度系数(Calculate the rock surface crack width and strike the surface roughness coefficient)

使用Matlab编程，对教材74页例3.3.1进行编程仿真。其中，正电压A的值、噪声方差值、每个码元周期内的采样点数N自行设定（可设置为可调的变量）。噪声值可使用Matlab中产生高斯随机数的函数来进行仿真。贝叶斯检测判决式中，先验概率P(H1)=P(H0)，判断错误的代价因子设为1，判断正确的代价因子设为0. 按照上述参数的设定进行仿真，实现对仿真数据的贝叶斯检测判决；循环生成仿真数据，并进行判决结果的统计，即记录判决正确的次数，估计正确判决的概率。(The use of Matlab programming, teaching materials 74 pages of 3.3.1 programming simulation. Among them, the value of positive voltage A, the variance of noise, the number of sampling points in each symbol cycle (N) can be set by itself (adjustable variable). Noise values can be simulated using the function of generating Gauss random numbers in Matlab. In the Bias detection decision, the prior probability P (H1) =P (H0), the factor of error judgment is set to 1, and the correct cost factor is set to 0. According to the simulation parameters and realize the judgment of Bayesian detection simulation data; generating cycle simulation data, statistics and decision, which records the correct number of judgment, the estimated probability of correct decision.)