FFT_analysis

牛顿迭代法用于求解非线性方程组，及求解范围(Newton iterative method for solving nonlinear equations, and solve the range)

单通道欠采样测量频率的程序 可以正确得到信号的频率(dantongdao.m)

8自由度的汽车模型,包括abs clutch 建立了动力学公式的模型，需要对几个积分器设置初值，避免代数环(vehicle model of 8 degrees)

基本的惯性导航解算过程以及摇摆条件下的惯性导航程序(Inertial navigation program under the basic inertial navigation solution process and the swing conditions)

An Evolutionary Routing Protocol for Dynamic Clustering of Wireless Sensor Networks using HCR

SVPWM控制仿真程序，经调试通过，与大家共分享，MATLAB7.1(SVPWM control simulation program by debugging through, and we were sharing, MATLAB7.1)

Optimization Techniques

这是一个说话人识别的程序，其中有十个说话人，识别率可达到90 。执行时，执行“laststep.m”(This is a speech recognition program, including dozens of speaker recognition rate can reach 90 . Implementation, implementation " laststep.m" )

％ 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)

说明：  Matlab车间动态调度PSO微粒群算法程序（优化目标为机器间隙时间）(Matlab Workshop Particle Swarm Optimization PSO dynamic scheduling procedures (optimization target machine clearance time))