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这里给出另一组对谱线校正的方法，其中包括了9种方法。(Here are the other group on the spectrum correction method, including nine kinds of methods.)

利用均匀分布产生高斯白噪声随机数，瑞利随机数，泊松随机数。附有报告~(The use of Gaussian white noise uniformly distributed random number generation, random number Rayleigh, Poisson random number. Accompanied by the report-)

地震数据读取程序，matlab编写，可以实现segy格式的读取(to read Seismic data of segy format ，Matlab。)

基于信息最大化的盲源分离，采用2路混合超高斯信号，分离效果明显(Based on information maximization blind source separation using 2-way mixed super-Gaussian signal, separation effect is obvious)

image processing procedures

Traz de volta os arquivos ocultos e potegidos do sistema dentro de um diretorio especifico

％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input data, n=number of observations, d=dimension of variable ％ k - maximum number of Gaussian components allowed ％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none) ％ maxiter - maximum number of iteration allowed ([] for none) ％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) ％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) ％ ％ Ouputs: ％ W(1,k) - estimated weights of GM ％ M(d,k) - estimated mean vectors of GM ％ V(d,d,k) - estimated covariance matrices of GM ％ L - log likelihood of estimates ％( EM algorithm for k multidimensional Gaussian mixture estimation Inputs: X (n, d)- input data, n = number of observations, d = dimension of variable k- maximum number of Gaussian components allowed ltol- percentage of the log likelihood difference between 2 iterations ([] for none) maxiter- maximum number of iteration allowed ([] for none) pflag- 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) Init- structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) Ouputs: W (1, k)- estimated weights of GM M (d, k)- estimated mean vectors of GM V (d, d, k)- estimated covariance matrices of GM L- log likelihood of estimates)

mimo的空时编码的源代码 在matlab环境下运行 4发1收 (the mimo empty encoded source code in Matlab environment, run four rounds of a received)

模拟2个独立窄带信号分别以20°，60°的方向入射到均匀线阵上，信号间互不相关，与噪声相互独立，噪声为理想高斯白噪声，阵元间距为入射信号波长的1／2，信噪比为20dB，阵元数为10，采样快拍次数为200。(Simulate two independent narrowband signals in the direction of 20 °, 60 ° of the incident on the ULA, among signal unrelated, independent noise, the noise is ideal Gaussian white noise, the array element spacing of the incident signal wavelength of 1/2, the signal to noise ratio is 20dB, the array element number 10, the sampling frequency of 200 snapshots.)

说明：  基于主动轮廓模型的虹膜图像定位算法研究及其matlab实现(Iris recognization, Matlab, based on snake,actice countours)