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贤哥的矩阵分析与应用习题解答，答案在手，前途永久。(Shane matrix analysis and application, the answer is in hand, the future permanent.)

电容层析成像的LBP算法演示程序，并带有详细的数据与说明(The LBP algorithm for capacitance tomography demonstrates the program with detailed data and instructions)

说明：  c语言用来进行数值计算的相关程序和论文，非常棒棒棒(C language for numerical calculation of the relevant procedures and papers, very good)

一个用于弹性接触分析的边界元fortran源程序(One for the analysis of elastic contact BEM fortran source)

说明：  关于多智能体系统一致性的程序，解微分方程(Consistency of multi-agent systems program)

电磁场数值计算中的差分法在matlab中的实现(The realization of difference method in numerical calculation of electromagnetic field in matlab)

用于进行电力系统的暂态稳定计算的基本算法和程序仿真(Basic algorithm and program simulation for transient stability calculation of power system)

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.)

说明：  VUMAT for Kinematic Hardening Plasticity

Spearman程序代码，可以用于分析相关性关系，挖掘数据之间的联系(Spearman program code)