Zbuild

利用最小二乘方法，对三维数据进行平面拟合，并对数据进行误差提出(least square plane fitting )

说明：  在学习数字信号处理算法程序中用VC编写的几个通用算法程序。 卷积计算/DFT与FFT实现/(In the learning process of digital signal processing algorithms using VC General Algorithm for the preparation of several procedures. Convolution calculation/DFT and FFT realization /)

求实对称矩阵的特征值特征向量，内有读入数据文件。(Realistic symmetric matrix eigenvalue eigenvector, there are read into the data file.)

C++的求阶乘的程序，对本科C++课程可能有些帮助(Factorial in C++ program, it maybe helpful for some C++ course)

数学最优问题中，拉格朗日乘数法（以数学家约瑟夫·路易斯·拉格朗日命名）是一种寻找变量受一个或多个条件所限制的多元函数的极值的方法。(In the mathematical optimization problem, the Lagrange multiplier method (named by the mathematician Joseph Luis Lagrange) is a method of finding the extremum of a multivariate function which is restricted by one or more conditions.)

曲线拟合的最小二乘法要解决的问题，实际上就是求以下超定方程组的最小二乘解的问题。(Least squares curve fitting to solve the problem, in fact, find the following overdetermined least squares solution for the problem group.)

ANSYS 分析一座预应力连续刚构桥的命令流，很实用哦(ANSYS analysis of a prestressed continuous rigid frame bridge command stream, and very practical!)

BP神经网络的整个训练过程,matlab编写的元胞自动机，独立成分分析算法降低原始数据噪声。( The entire training process BP neural network, matlab prepared cellular automata, Independent component analysis algorithm reduces the raw data noise.)

非线性有限元及程序这本书,很有用的，程序也很全面(NONLINEAR FINITE ELEMENT AND PROGRAM)

Orthogonal Polynomials Approximation 数值分析，计算正交基多项式的系数 (Given a function f and a set of m >0 distinct points . You are supposed to write a function to approximate f by an orthogonal polynomial using the exact function values at the given m points with a weight assigned to each point . The total error must be no larger than a given tolerance. Format of function int OPA( double (*f)(double t), int m, double x[], double w[], double c[], double*eps ) where the function pointer double (*f)(double t) defines the function f int m is the number of points double x[] contains points double w[] contains the values of a weight function at the given points x[] double c[] contains the coefficients of the approximation polynomial double*eps is passed into the function as the tolerance for the error, and is supposed to be returned as the value of error. The function OPA is supposed to return the degree of the approximation polynomial. Note: a constant Max_n is defined so that if the total error is still not small enough when n = Ma)