BEM

说明：  利用matlab求解方程，方程求解并画图(Equation solving and drawing)

说明：  基于力密度法的索杆张力结构找形程序，压缩包力有算例(power density method based on the structure of cable-form-finding procedures, compressed power is counting cases)

国外的地震有限元程序，美国伯克利大学的，非常经典(Earthquake abroad finite element program, the United States Berkeley, very classic)

概念格的构造问题是形式概念分析应用的前提。由于概念格的时空复杂度随着形式背景的增大而可能指数性的增大，有关概念格的生成问题一直是形式概念分析应用研究的一个重点。国内外的学者和研究人员对此进行了深入的研究，提出了一些有效的算法来生成概念格，这些算法一般可分为两类：批生成算法(Batch Algorithm)和渐进式生成算法(Incremental Algorithm )。。 (Concept lattice structure problem is the premise formal concept analysis applications. Since the concept of space-time lattice with the increasing complexity of the form and context may increase exponentially, generating questions about the concept lattice has been a focus of formal concept analysis applied research. Domestic and foreign scholars and researchers conducted a thorough study made a number of efficient algorithms to generate the concept lattice, these algorithms can be divided into two categories: batch generation algorithm (Batch Algorithm) and progressive generation algorithm (Incremental Algorithm ). .)

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.)

这个帖子中我想讨论的是移动窗口多项式最小二乘拟和平滑方法，粗糙惩罚方法，以及kernel平滑方法。(Posts in this discussion I think are moving window least squares polynomial fitting smoothing method, crude methods of punishment, as well as the kernel smoothing method.)

说明：  umat abaqus plasticity

蒙特卡洛资料，对于编写概率计算问题有较多的帮助，希望能帮到需要的人。(Monte Carlo)

ansys 求解桥梁结构弯矩响线的命令流，非常实用(ansys solving the stream of the bridge structure bending ring line command is very useful)

电磁场的时域有限元仿真,用于学习电磁场的时域计算。(Time domain electromagnetic finite element simulation for learning time-domain electromagnetic field calculation.)