rosenbergtrustregion

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.)

同伦算法解非线性方程组，构造不动点问题,并从不同的初始点出发运行程序。(To solve nonlinear equations with homotopy algorithm，constructing a fixed foint progrem.and from the different starting point to run the program. )

几个kalman滤波的例程 适合初学者使用 并有优化建议(Several kalman filter routines suitable for beginners to use and has optimization tips)

说明：  线性代数及其应用 第4版 1-Linear Algebra and Its Applications 4ed.MIT Gilbert Strang(1-Linear Algebra and Its Applications 4ed.MIT Gilbert Strang)

含约束的优化问题求解案例，算法简单，求解很方便实用(Constrained optimization problem solving case, the algorithm is simple, easy to solve, practical)

COMSOL工程案例的英文书籍，亚马逊网站可查，售价不费。(COMSOL project case of English books, Amazon website can be found, the price is not cost.)

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.)

求二元一次方程组的解,简便算法的过程及计算(Solving linear equations group，Process and simple calculation algorithm)

合肥工业大学数值分析（计算方法A）中高斯—塞德尔算法的实现(Gauss- Seidel Algorithm)

EKF uKF的matlab工具箱，适合做非线性滤波的仿真计算。(EKF uKF the matlab toolbox for nonlinear filter to do the simulation.)