alidity-Measures-for-the-Fuzzy-Cluster

在matlab7.0下沒問題，有性趣的人可以拿回去參考參考。(Matlab7.0 no problem in the next, there are interested people can go back and refer to the reference holding.)

16 QAM误码曲线仿真,运用Matlab语言(16 QAM BER curve simulation ,based on MATLAB)

通过提取不变量特征来实现两幅图像之间的匹配(matching by two pointwhich are sift)

维纳噪声抑制，设计p阶的最优FIR维纳滤波器，估计平均平方误差， 试针对p=12的情况，分别取几个不同的权值(如0.1, 0.5, 1.0)，研究这时的噪声抑制性能。(Wiener noise suppression, the optimal design of p-order FIR Wiener filter, estimated mean square error, try the case for p = 12, respectively, the right to take several different values (such as 0.1, 0.5, 1.0), study time noise suppression performance.)

pid controleur with optimisation

圆卷积与线卷积在FIR中的实现，通过程序还开深刻理解两者间的差别和各自优劣。 1.圆卷积用在被截出的某段数据中，此时，长度应该定为和输入数据长度一致（一般输入数据大于hn的数），这时圆卷积结果相当于某段被截断出来的数据以非截断的方式经过滤波而得出的结果；线卷积用在各自独立的，离散的数据中，若截断数据也用线性卷积来计算，那么就相当与这部分数据是与源数据是独立的， 得出的结果时域两端会变长，但频谱基本上一样的。差别可以想象。 2.注意圆卷积最开始的输入数据的次序，构造矩阵时要注意。(Circular convolution with the line convolution in the FIR implementation, the program also opened a deep understanding of the difference between the two and their respective pros and cons. A circular convolution with cut out a certain period of data At this point, the length should be set for the same length as the input data (typically input data greater than hn the number), when the circular convolution is equivalent to a certain the results of the truncated data to the non-truncated filtered line convolution with a separate, discrete data, truncated data with a linear convolution calculation, then the equivalent of this part of the data is independent of the source data, the results of both ends of the time domain becomes long, but the spectrum is basically the same. The difference can imagine. Note that the order of the circular convolution of the input data to construct matrix.)

自适应（LMS）算法在噪声抑制中的应用。在仿真中，原始信号选为sin((0.2*pi)*t), 噪声信号采用标准白噪声，延迟D=1，收敛因子分别是u=0.001和u=0.3(Adaptive (LMS) algorithm in noise suppression application. In the simulation, the original signal is selected sin ((0.2* pi)* t), noise signal using the standard white noise, the delay D = 1, respectively, convergence factor u = 0.001 and u = 0.3)

基于模拟退火的粒子群算法，具体问题可以参见十一届华为杯数学建模E题乘车物流规划问题前三问(This is simuAPSO,very good！)

采用数字图像主分量分析（PCA）算法实现人脸识别（身份认证或分类）(Principal components using digital image analysis (PCA) algorithm for face recognition (identity or category))

estimate the number of source using AIC and MDL criterion.