svmmatlabachievesystem

单闭环转速负反馈直流调速系统仿真 simulink模型，可仿真，可运行，有源码(Single-loop speed control system based on negative feedback DC)

numerical code for matlab analytical bisec differentiation F FALSEPOS fixedpoint

Base paper is regarding robust face recognition

kolmogorov功率谱反演，次谐波补偿的方法生成大气湍流相位屏(kolmogorov phase screen,kolmogorov,including subharmonic)

Financial risk analysis on Matlab monte carlo simulation, stock index simulation for geometric Brownian motion, GBM.

经验模式分解源码 学习希尔波特黄变换的参考程序 源于Internet网络，欢迎传播交流！(Empirical mode decomposition source learning Hilbert Huang Transform reference procedures from Internet network, welcomes the dissemination of the exchange!)

EOF分析，对于数据进行EOF的转换分析(EOF analysis)

a matlab simulink simulation for sine wave generation

张德丰matlab小波分析源代码，从信号时-频联合分析引入小波变换，将信号的多分辨率分析及Mallat算法作为全书的重点，并在此基础上，进一步阐述了双正交小波多分辨率分析、小波包多分辨率分析、提升小波应用，还讲述了小波分析在奇异性检测、去噪及数据压缩中的应用。(Zhang Defeng Matlab wavelet analysis of the source code from the signal- frequency joint analysis of the introduction of wavelet transform, multi-resolution analysis of the signal and Mallat algorithm as the focus of the book, and on this basis, further elaborated biorthogonal wavelet multi-resolution analysis wavelet packet multi-resolution analysis, the lifting wavelet applications, but also about the application of wavelet analysis in the singularity detection, de-noising and data compression.)

％ 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)