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Minh Do《Contourlet toolbox》(Contourlet变换影像处理工具箱)(Minh Do《Contourlet toolbox》)

入侵性杂草算法，连续型，多目标，多维函数优化。(invasive weed 0ptimization is a good optimal tools for any continual problem. IWO has been successfully applied to several electromagnetic optimization problems)

lcs3码系统仿真程序，matlab7.0编译通过，介绍lcs3码在不同参数下，系统信号输出的不同结果(lcs3 code system simulation program, matlab7.0 compiler passed, introduce lcs3 code in different parameters, the system signal output of the different results)

Find peaks in all waveforms. used in matlab. The peaks can be maximum and minimum.

用matlab仿真的BPSK_OFDM_Simulation的代码(Simulation using matlab code BPSK_OFDM_Simulation)

natural convection slution using matlab

产生两不迥频率的信号，并对两信号作复数FFT变换，找出频率为50Hz的信号对其进行能量计算(Two distant signal is not generated frequency, and two signals for complex FFT transform to identify the frequency of 50Hz signal to calculate its energy)

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)

ser的比较实现基于mmse_mse和LS_mse (SER compare)

codage programmes pour la parole