Scientific-Calculator

用vc++编写的具有计算齿轮误差的软件，并能判断是否合格(Prepared using vc++ error with computing gear software, and to determine eligibility)

说明：  数学建模工具箱 有丰富的数学建模模型，全部用matlab语言编写(Mathematical Modeling Toolbox)

abaqus中的三微裂纹扩展，一起学习下(the abaqus of three micro-crack propagation, with learning under)

张学工老师模式识别第一次作业，用贝叶斯方法和正态分布的监督参数估计对身高体重二维数据进行性别分类(Zhang engineering teacher pattern recognition for the first time operations, using Bayesian methods, and the supervision of normal height and weight of two-dimensional parameter estimation of the gender-disaggregated data)

根据给定的等距结点上的函数值与一阶导数值, 用埃尔米特等距插值公式计算指定插值点处的函数值。(According to the given equidistant nodes function value with a first derivative values, with equidistant interpolation Hermite interpolation formula specified function value at the point.)

用于学习LBM对流体的研究，可以加深对LBM的理解(LBM fluid)

计算流体力学，HLL格式的一个算例，可以直接计算，适合初学者，易懂，每步有说明。(The calculation of an example of fluid dynamics, HLL format, can be calculated directly, suitable for beginners, easy to understand each step is described.)

共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(Conjugate gradient method (Conjugate Gradient) is between the steepest descent method between the method and Newton' s method, it takes only a first derivative information, but to overcome the steepest descent method convergence slow shortcomings, but also to avoid the Newton method needs to be stored Hesse and disadvantages of computing inverse matrix and the conjugate gradient method is not only one of the most useful methods to solve large linear equations, solution of large-scale nonlinear optimization is one of the most effective algorithm. In various optimization algorithm, conjugate gradient method is a very important one. The advantage is that a small amount of memory required, with step convergence, high stability, and does not require any external parameters.)

计算电磁学基础教材， 包括MOM FEM FDTD(fundmental materail for beginner include MOM FEM FDtd)

此源码包是我本学期最优化理论课程的大作业，其中包括了我自己写的以下常用最优化算法的实现代码：最速下降法，牛顿法，非线性最小二乘法，DFP法。fun1，fun2是两个测试函数。谢谢！(This is my source packages optimization theory this semester courses in large operations, including my own to write the following commonly used optimization algorithm code: steepest descent method, Newton method, nonlinear least squares method, DFP method. fun1, fun2 are two test function. Thanks!)