SADFSA

Cao法求嵌入维数ｍ，相空间重构理论需计算最优嵌入维数ｍ和最佳延迟时间τ, 重构相空间。(Cao method of embedding dimension of phase space m, to calculate the optimal embedding dimension m and the optimal time delay of phase space reconstruction theory.)

VC++与Matlab混合编程时，所需的lib库文件压缩包(VC++ and Matlab mix program，need liblibrary rar)

1．熟悉matlab基础操作。 2．能够用Lagrange插值, Newton插值法对函数表进行一次、二次、三次插值，体会各种插值方法不同的特点。 (A. Familiar with matlab underlying operating. Two. With Lagrange interpolation, Newton interpolation function table once, quadratic, cubic interpolation, and appreciate the different characteristics of the various interpolation methods.)

GUI接口编程设计经典源码资料GUI Interface Programming classic source data(GUI Interface Programming classical source information GUI Interface Programming classic source data)

fluent syamlal-obrien模型(fluent syamlal-obrien model)

说明：  一些有关最优控制理论的控制实例程序集和仿真 (Control instance assembly of the optimal control theory and simulation)

一个二维的fdtdc++编写的程序，较完整，带有pml边界条件。感兴趣的可以下载看看。(A two-dimensional fdtdc++ preparation procedures, more complete, with pml boundary conditions. Interested can download to see.)

vc与matcom混合编程实例，里面包含了matcom将matlab m文件转换成C++文件的例子，然后在vc中调用，画图，并借助matlab在vc中对音频文件进行幅度和相位分析(Vc mixed with matcom programming examples, containing the matcom transform matlab m file into the c++ file example, and then call in the vc, drawing, and with the help of matlab in the vc of amplitude and phase analysis was carried out on the audio file)

k means 聚类聚类聚类聚类聚类聚类聚类聚类聚类(k means)

用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)