giumiu_v41

转子动力学研究中完整的支承松动数值仿真程序(Rotor dynamics study supports the complete relaxation of numerical simulation program)

基于解相干的MUSIC源程序 矩阵分解算法 Toeplitz算法 矢量奇异值法 双向空间平滑MUSIC源程序(Based on decorrelation MUSIC algorithm source Toeplitz matrix factorization algorithms singular value vector bi source spatial smoothing MUSIC)

实现线性代数的矩阵运算的C++程序，矩阵计算器。(Linear algebra matrix operations C++ procedures matrix calculator.)

适用于Engine计算的经典PISO算法(the classic PISO algorithm for the Engine calculation )

基于配电网络辐射型的前推回代潮流计算程序，包括分层等内容(And backward substitution based on the radiation type of distribution network before flow calculation procedures, including the contents of the stratification)

基于RWG基函数的矩量法分析偶极子天线的辐射特性，全部程序每行本人都有详细注释，清晰容易理解，出来的结果与理论分析完全一致。(RWG basis function method of moments-based analysis of the dipole antenna radiation characteristics, all the procedures every line I have detailed notes, clear and easy to understand, exactly the same out of the results with the theoretical analysis.)

计算方法程序:多项式拟合(Calculation procedure: Polynomial Fitting)

常用的积分函数，能够很方便的解决数值积分的问题(Commonly used integral function, can be very convenient to solve the problem of numerical integration)

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.)

电容层析成像Tikhonov算法的演示实例，带有详细的说明(An example of a demonstration of the Tikhonov algorithm for capacitance tomography, with a detailed description)