FFT842

说明：  Neville插值算法，xa为自变量数组，xy为因变量数组；x为待插值的自变量(Neville interpolation algorithm, xa array as variables, xy array as the dependent variable x for the independent variables to be interpolated)

多项式的加减法运算，输入的多项式带有未知数x和数字(Polynomial addition and subtraction calculations)

基于FLUENT软件的一些常用UDF实例，比较有帮助(udf example)

弗洛伊德算法最短距离的实现，输入为邻接矩阵，输出为最短距离矩阵。(Freud' s realization of the algorithm for the shortest distance, enter the adjacency matrix output for the shortest distance matrix.)

这是一个小型计算器，功能强大，用户输入想要计算的数据，即可自行计算出结果。(This is a program about calculator,and it is very userful.)

半参数回归模型在测绘领域中的应用，先利用多期数据构建半参数回归模型，然后再预报未来多期数据(Semiparametric regression model applied in the field of surveying and mapping, the first use of multi-phase data to construct semi-parametric regression model, and then predict the future multi-phase data)

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)

Fractional knapsack problem, Greedy algorithm

This directory contains code implementing the K-means algorithm. Source code may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS program accepts input consisting of vectors and calculates the given number of cluster centers using the K-means algorithm. Output is directed to the screen. Usage for KMEANS is: KMEANS SOURCEFILE <enter> The format of the source file is: NPat - Number of patterns (int) SizeVect - Size of vector (int) NClust - Number of cluster centers(int) vect[1,1] ... vect[1,SizeVect] - vector 1 (real) vect[2,1] ... vect[2,SizeVect] - vector 2 (real) . . . . . . vect[NPat,1] ... vect[NClust,SizeVector] - vector N (real) To compile: ICC KMEANS.CPP <enter> (This directory contains code implementing the K-means algorithm. Source code may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS program accepts input consisting of vectors and calculates the given number of cluster centers using the K-means algorithm. Output is directed to the screen. Usage for KMEANS is: KMEANS SOURCEFILE <enter> The format of the source file is: NPat - Number of patterns (int) SizeVect - Size of vector (int) NClust - Number of cluster centers(int) vect[1,1] ... vect[1,SizeVect] - vector 1 (real) vect[2,1] ... vect[2,SizeVect] - vector 2 (real) . . . . . . vect[NPat,1] ... vect[NClust,SizeVector]- vector N (real) To compile: ICC KMEANS.CPP <enter> )

基于TMS320LF2407的FFT算法的实现及应用(TMS320LF2407 of the FFT algorithm based on Implementation and Application of)