newspring

用MATLAB实现单因素/两因素重复测量方差分析，自带工具包中只有非重复测量的方差分析函数ANOVA。anova_rm实现单因素；rm_anova2实现两因素( function stats = rm_anova2(Y,S,F1,F2,FACTNAMES) Two-factor, within-subject repeated measures ANOVA.For designs with two within-subject factors. function [p, table] = anova_rm(X, displayopt)Single factor, repeated measures ANOVA.)

计算fft，输出频谱，相位，模值,Calculation of FFT, the output frequency, phase, amplitude,

一个简单的CZT chirp-Z变换例程(a simple example of CZT)

快速傅立叶变换，双边傅里叶变换的LabVIEW程序(Fast Fu Liye transform, bilateral Fourier transform of the LabVIEW 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)

数值分析中三次样条插值算法，运行稳定，并能画出最后的插值曲线(Numerical Analysis of cubic spline interpolation algorithm, running stability, and can draw the final curve interpolation)

matlab code for exponential PSO

说明：  所给的m文件中有详细的构造三对角分块矩阵的方法，而且构造的分块矩阵采用的是稀疏存储的方法，适用于大型三对角分块矩阵的构造(There are detailed methods to construct tridiagonal block matrix in the given m file, and the method of sparse storage is used to construct the block matrix, which is suitable for the construction of large tridiagonal block matrix.)

关于simple算法，希望站长能够让小弟加入这个学习的行列。(on simple algorithms, hoping to let the younger station to join the ranks of the study.)

从数据样本中随机选取一本分数据，运用K2算法进行贝叶斯网络结构学习(A sub-data randomly selected the data samples, using K2 Bayesian network structure learning algorithm)