PLS_NIPALS

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)

说明：  介绍线性算子的基本概念的文章,这是书里面的一个章节(Foundation of linear operator theory)

矩阵,复数自定义数据类型的C++实现,矩阵求逆采用牛顿法,(The matrix, complex number custom data type C realization, the matrix inverse uses the Newton method,)

可以实现十几位整数的四则运算，效率也较好(Four operations can be more than a dozen integer,and the efficiency is better)

稀疏矩阵算法及其程序实现(杨绍祺+谈根林)，有解决稀疏矩阵需要的朋友可以好好认真的看一下(Sparse matrix algorithm and program implementation (Yang Shaoqi+ Tan root forest), solve sparse matrix can be a good friend in need a serious look at)

非极点对称的经验模态分解matlab计算程序(Non - pole symmetry empirical mode decomposition matlab calculation program)

用蒙特卡洛模拟的方法计算美式期权的价格以及基本描述,能量熵的计算，sar图像去噪的几种新的方法。( Monte Carlo simulation method of calculating the American option price and basic description, Energy entropy calculation, Several new methods sar image denoising.)

利用FFT估计正弦信号的频率,要估计一个叠加了高斯白噪声的正弦信号 的频率 ，可以通过对x(n)做傅里叶变换，得到频谱图，找出幅度的最大值对应的频率值 ，进行多次变换，求出均方误差 。改变信噪比SNR，通过仿真可以得出随着信噪比增加，均方误差减小。(Sinusoidal signal using FFT frequency estimation, to estimate a Gaussian white noise superimposed on the frequency of sinusoidal signals, can be achieved by x (n) be the Fourier transform to get spectrum to identify the magnitude of the frequency value corresponding to the maximum , several transformations, find the mean square error. Change the signal to noise ratio SNR, the simulation can be drawn as the SNR increases, the mean square error decreases.)

扩展年有限元的相关文献，内含7篇综述，完整概括扩展有限元的发展。做这个方面的可以看一看。(Extended Finite element of the relevant literature, containing 7 review, complete the development of finite element summed expansion. So this area can take a look.)

其基本思想是取B样条函数 为及基函数，在[a,b]中均匀划分区间，xi=a+ih,h=(b-a)/n,由于三次样条函数空间是n+3维的，所以把分点扩充到x-1,xn+1,则任意三次样条函数可用 线性组合来表示：(The basic idea is to take B-spline function and basis functions in [a, b] in the evenly divided intervals, xi = a+ ih, h = (ba)/n, because the cubic spline function is n+3 dimensional space , so the expansion points to the x-1, xn+1, then any cubic spline function can be expressed as a linear combination:)