bi_sipls

说明：  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 Gradient) is a method between the steepest descent method and Newton's method. It only uses the first derivative information, but overcomes the disadvantage of slow convergence of steepest descent method, and avoids the disadvantage of storing and calculating Hesse matrix and solving inverse of Newton's method. Conjugate gradient method is not only one of the most useful methods to solve large-scale linear equations, but also the most effective method to solve large-scale nonlinear optimization One of the algorithms of. Among all kinds of optimization algorithms, conjugate gradient method is very important. It has the advantages of small storage, step convergence, high stability and no external parameters.)

贪婪算法，可以用于资源分配等许多数学问题和工程问题中(Greedy algorithm)

牛顿迭代法求解非线性代数方程组的主要思想是将非线性函数线性化(Newton iteration method for solving nonlinear algebraic equations nonlinear function of the main idea is to linear)

fitness,适应度函数，计算适应度函数，(fitness, fitness function, calculate the fitness function,)

基于最小二乘的多项式拟合法的GPS周跳探测程序(Based on the least square polynomial fitting method of GPS cycle slip detection program )

BESO的python程序，对于进行abaqus的二次开发很有帮助，这样可以将有限元单独在abaqus中进行处理，而优化算法则采用python进行编写(BESO python program, for the secondary development abaqus helpful, so that the finite element can be handled separately in abaqus, while the optimization algorithm is written in python)

说明：  基于matlab实现的拉格朗日插值函数，牛顿插值函数代码。(Based on MATLAB Lagrange interpolation function, Newton interpolation function code)

卡尔曼滤波程序用于时间序列预测，结构简单程序易懂(kalman filter for prediction)

分享一个外国人编写的FDTD程序,可以用来计算微带线和微带贴片天线,程序中采用的是均匀网格划分,但也可以在容易地在它基础上改写成非均匀网格.其边界条件与Sheen的程序不同,这里采用二阶技术.(Prepared to share a foreigner FDTD procedures, can be used to calculate the microstrip lines and microstrip patch antenna, the procedure used is uniform mesh, but can also easily rewrite it into the basis of non-uniform grid. its boundary conditions with different processes and Sheen, where second-order technology.)

分别对beta估计值模拟分析、非中心对称分布、卡方拟合优度检验、筛选抽样随机数抽取、有限样本性质模拟这5个内容进行了编程说明(The five contents of beta estimation simulation analysis, non-centrosymmetric distribution, chi-square goodness-of-fit test, random number extraction of screening sampling and Simulation of finite sample properties are explained by programming.)