Inpaint_nans

基于视觉诱发电位的脑电信号的频率和相位的检测，用于得到受试者的看到的数字。(SSVEP brain signal anlaysis codes. )

c++通用技能编码能力提升：组件安装管理程序，已测试。(c++ generic skills coding capacity building: Component Installation Manager has been tested.)

关于matlab的矩阵数据结构部分，可以更深入掌握，和符号计算相衔接(About matlab matrix data structure part, you can have a better understanding, and symbolic computation convergence)

说明：  QC-LDPC的主程序，IEEE802.16e标准，考察迭代次数对误码率的影响(Various encoding and decoding methods of LDPC)

数值分析的实验，拉格朗日、分段线性、三次样条等(Analysis of the experiment, Lagrangian, piecewise linear, cubic spline, etc.)

外螺旋矩阵的递归和非递归C编程方法 笔试中经常出现的题(Spiral Matrix outside the recursive and non recursive methods written in C programming problems often appear in)

说明：  了解matlab编程的机制，里面包含了80多个matlab程序，是初学者的必备资料。(Matlab program to understand the mechanism, which includes more than 80 matlab program, is essential information for beginners.)

dancuangkoupaiduixitong dancuangkou paidui xitong (single-window ticketing system simulation program )

分解图像像素值为二进制，对图像进行二进制为基础的DNA编码(Decomposition of the image pixel value is binary, binary image based on the DNA coding)

MATLAB 牛顿下山法的一个小程序，原理就不详细说了。因牛顿迭代法受初值选取的限制，为防止迭代发散，对迭代过程再附加一项要求:|f(x(k+1))|<|f(x(k))|,将牛顿法迭代的结果:x(k+1) =x(k)-f(x(k))/f (x(k))和前一近似值x(k)适当加权平均做为新的改进值:x(k+1)=u*x(k+1) +(1-u)*x(k),其中u(0<> 迭代时u取1开始，逐次减半计算，直至附加要求符合为止。实例计算中x(k)=x(0)不变，只更新u和x(k+1)，直至:|f(x(k+1))|<|f(x(k))|（即|f(x(1))|<|f(x(0))|)，然后更新下山因子为u=1,继续以牛顿法迭代。(MATLAB Newton-down a small program, the principle is not explained in detail. Newton iteration by the initial value of the selected limit, in order to prevent additional iterative divergence, the iterative process a request: | f (x (k+1)) | < | f (x (k)) | Newton iteration Results: x (k+1) ' = X (k)-f (x (k))/f' (x (k)) and a previous approximation x (k), appropriately weighted average as a new improved value: x (k+1 ) = u* x (k+1) ' + (1-u)* x (k), where u (0 < u> iteration take successive calculated at 50 until the additional requirements found so far. examples of calculation of X ( k) = x (0) unchanged profile u and x (k+1, hungry) until: | f (x (k+1)) | < | f (x (k)) | (i.e. | f (x (1)) | < | f (x (0)) |), then profile downhill factor for u = 1, to continue to Newton iteration.)