Fitting_Gumbel

数据挖掘中，关联规则的例子，源码， arview算法的应用实例(data mining, association rules example, the source, the algorithm arview Application)

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.)

用C++编写的一维和二维快速傅里叶变换程序(Prepared with C++ one-dimensional and two-dimensional fast Fourier transform procedure)

最小二乘法拟合形如f(x)=(a+bx)/(1+cx)的函数（9.2.2(1))，并解决人口预测问题(9.2.2(2))(Least squares fit of the form f (x) = (a+bx)/(1+cx) function (9.2.2 (1)), and to solve the population prediction problem (9.2.2 (2)))

使用正交多项式完成数据拟合。程序对读入的gps采样点完成曲线拟合。()

最小二乘法数据处理软件，翻遍计算的程序，应用于各种优化算法(math caculateor)

Levenberg Marquardt算法的matlab代码,简洁无误,结构清晰,便于快速学习。( LevenbergMarquardt algorithm matlab code, simple and correct, clear structure, easy to learn quickly.)

FFT with fix point 2*N

里面包含了随机矩阵理论里经典的仿真，如marcenko-pastur law,tracy-widom law等(It contains some classical simulationa in the random matrix theory，such as marcenko-pastur law,tracy-widom law)

matlab实现捷联惯性导航解算，四元数更新姿态矩阵。(SINS solver matlab)