Job-niantan-s-t-1

说明：  用于三维条件下的推板造波法udf,冲程与周期可修改，附带消波udf和cas文件(generating waves with pushboard under 3D condition)

5个子函数，包括格拉布斯剔除异常值函数，牛顿插值法函数，拉格朗日插值法函数，希尔排序函数，莱以特准则剔除异常值函数，函数方便移植。(5 sub-functions, including functions Grubbs outliers removed, Newton interpolation function, Lagrange interpolation function, Hill sort function, Levin special criteria to exclude outliers, function to facilitate transplantation.)

用于处理电力系统中含有4个节点的随机潮流计算(Four nodes to deal with the random flow calculation)

说明：  分数低阶协方差谱的MATLAB程序，含4种计算分数低阶协方差谱的估计方法(Fractional lower order covariance spectrum MATLAB program, including four kinds of calculation of fractional lower order covariance spectral estimation method)

wolfe程序模块的C++算法，可以重复使用,对于解决一维搜索是很好的..(C++ algorithm wolfe program modules can be reused for solving one-dimensional search is good ..)

对于协方差矩阵的一种计算方法，对于地震中的反演约束算法能起到很好的作用。(For a kind of covariance matrix calculation method)

说明：  牛顿法又称牛顿-拉弗森方法（Newton-Raphson method），是一种在实数域和复数域上近似求解方程的方法。本程序收敛速度快，迭代步数可取大一些(Newton method, also known as Newton-Raphson method, is an approximate method for solving equations in real and complex fields. The program has fast convergence speed so the number of iteration steps can be larger.)

隐式及显示技术模拟复合材料结构的固化，UMAT程序(Cure Simulation of Composite Structures Applying Implicit and Explicit FE Techniques)

用C语言程序通过先随机选取K个对象作为初始的聚类中心。然后计算每个对象与各个种子聚类中心之间的距离，把每个对象分配给距离它最近的聚类中心。聚类中心以及分配给它们的对象就代表一个聚类。一旦全部对象都被分配了，每个聚类的聚类中心会根据聚类中现有的对象被重新计算。(C Programming Language by first randomly selected the K object as initial cluster centers. And then calculate the distance between each object and each seed cluster center, and assign each object to its nearest cluster center. Cluster centers, and the object assigned to them on behalf of a clustering. Once all the objects are assigned to each cluster cluster centers will be based on the existing object clustering is recalculated.)

关于复数矩阵求导的一本经典书籍“Complex-valued_matrix_derivatives”的电子版(About the electronic version of the complex matrix derivation of a classic book " Complex-valued_matrix_derivatives" )