FRFT_test_program

this is matlab pdfor pprobality theory which is implemetatde in matab 7,6

this is lpcc matlab code

Capon波束形成，应用于雷达，通信领域(Capon beamforming)

说明：  双线性内插,图像放大缩小，简单容易学，好理解，上手快(Bilinear interpolation, image zoom, simple and easy to learn, easy to understand, quick)

说明：  通过Monte Carlo仿真，说明DS扩频信号在抑制正弦干扰方面的有效性。用一均匀随机数发生器产生某个二进制信息符号的序列，每个信息比特重复Lc次。 包含文件：DS_restrain_interference.M SS.M(through Monte Carlo simulation, note DS spread spectrum signal sinusoidal interference in inhibiting the effectiveness. Using a uniform random number generator produce a binary sequence information symbols, each bit of information to repeat Lc times. Documents include : DS_restrain_interference.M SS.M)

手把手教你如何用matlab调用系统程序,并自动控制电脑定时关机(Taught you how to use matlab call system procedures, and automatic computer shutdown timer)

repval(X) finds all repeated values for input X, and their attributes. (The input may be vector, matrix, char string, or cell of strings Y=repval(X) returns the repeated values of X [RV, NR, POS, IR]=repval(X) returns the following outputs RV : Repeated Values (sorted) NR : Number of times each RV was repeated POS : Position vector of X of RV entries IR : Index of repetition Example: X=[1 5 5 9 5 5 1] [RV,NR,POS,IR]=repval(X) Output: RV = [1 5] Numbers 1 and 5 are repeated values NR = [2 4] Respectively repeated 2 and 4 times POS = [1 7 2 3 5 6] Position index of X for repeated values IR = [1 1 2 2 2 2] Corresponding to which index of RV )

张学工模式识别课件清华大学出版社。word版本(Zhang workers Pattern Recognition Courseware)

利用禁忌搜索算法求解0-1背包问题。禁忌搜索算法相比其他搜索算法更优，设置藐视规则来避免陷入局部最优解。(Solve 0-1 Knapsack Problem based on Tabu search. The tabu search algorithm is superior to other search algorithms and sets contempt rules to avoid falling into local optimal solutions.)

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.