MatlabTutorial

说明：  利用FFT快速算法来实现二维图像基于匹配追踪算法的稀疏分解。(Fast Algorithm for the use of FFT to achieve two-dimensional image matching tracking algorithm based on sparse decomposition.)

3phase fault in synchronous generator

this file contain the matlab code and source code file .it is used for separation of lung sound from heart sound

for Counting all repetitions of each elements repeated occurrences within a vector

基于平移不变小波变换的电力时间序列预测，结合多层感知器（MLP）神经网络， 预测精度很好。(Electricity demand time-series forecasting program Based on shift-invariant wavelet transform features )

singular spectrum analysis

模拟渗流集群效应的基本规律，欢迎大侠们的指导和讨论(Simulation of the basic rules of the seepage cluster effect, welcome the guidance and discuss the warrior)

XOR using Neural network

计算给定时间序列的最大Lyapunov指数(compute the maximal Lyapunov exponent of a time series)

function [L,C] = kmeans(X,k) KMEANS Cluster multivariate data using the k-means++ algorithm. [L,C] = kmeans(X,k) produces a 1-by-size(X,2) vector L with one class label per column in X and a size(X,1)-by-k matrix C containing the centers corresponding to each class. Version: 07/08/11 Authors: Laurent Sorber (Laurent.Sorber@cs.kuleuven.be) References: [1] J. B. MacQueen, "Some Methods for Classification and Analysis of MultiVariate Observations", in Proc. of the fifth Berkeley Symposium on Mathematical Statistics and Probability, L. M. L. Cam and J. Neyman, eds., vol. 1, UC Press, 1967, pp. 281-297. [2] D. Arthur and S. Vassilvitskii, "k-means++: The Advantages of Careful Seeding", Technical Report 2006-13, Stanford InfoLab, 2006.