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染色体识别与统计,识别其中的染色体并统计其数目，我们采用Matlab平台提供的一些图像处理函数.(Chromosome identification and statistics, to identify the chromosome and the number of statistics, we have adopted a Matlab platform provides a number of image processing functions.)

tests on simulink-matlab, crating filters parallel or cascade

很好的实用的随机微分方程求解工具箱，可以用来求解随机微分方程，还可以用于金融工程应用经济学等(Good practical stochastic differential equation toolbox)

两部传感器，相互采用CA-CFAR性能分析，并比较了不同融合准则下的性能(Two sensors each other using the CA-CFAR performance analysis, and compare the performance of different fusion criterion)

apsk软判决算法的仿真，根据星座特点进行算法的简化，减低复杂度(Simulation apsk soft decision algorithm based on the characteristics of the constellation simplified algorithm to reduce the complexity of)

杂波环境下基于EKF的多传感器的数据融合(Clutter environment EKF-based multi-sensor data fusion)

使用matlab研究光脉冲在光纤中的传播(ssft for nls by matlab)

外文资料里面的源代码，验证可用，小波包分析提取振动信号中的特征频率。( Foreign materials inside the source code, Verification is available, Wavelet packet analysis to extract vibration signal characteristic frequency.)

cl3多小波也是一个比较热门的多小波，应用的也比较广泛。(Multiwavelet CL3 is a more popular Multiwavelet, and more extensive applications.)

％ 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)