混合扩频DS/FH仿真程序kuopin

arma模型的matlab谱估计实现，较详细(arma model spectrum estimation matlab implementation)

Contourlet Toolbox (Version 2.0) Demos DECDEMO Demonstrates contourlet decomposition and reconstruction NLADEMO Demo for contourlet nonlinear approximation. NLADEMO2 Nonlinear approximation demo using only the finest scale DENOISEDEMO Denoise demo Main functions: Contourlets pyramidal directional filter bank PDFBDEC Pyramidal Directional Filter Bank (or Contourlet)

三维点云法向量估计综述由于获取方便、表示简单、灵活等优势，点云逐渐成为常用的三维模型表示方法之一。法向量作为点云必不可少的属性 之一，其估计方法在点云处理中具有重要的位置。另一方面，由于点云获取过程中不可避免的噪声、误差和遮挡，点云中通常含 有噪声、外点和空洞，并且部分采样模型如CAD模型，也会存在尖锐特征，这些都给法向量估计提出了挑战。对当前已有的点云 法向量估计算法进行综述，分析其原理及关键技术，着重分析它们在处理噪声、外点和尖锐特征等方面的能力并给出比较，最后 为未来研究提供了一些建议(The three-dimensional point cloud normal vector estimation summarized obtain convenient, represents a simple, flexible, and becoming one of the methods commonly used three-dimensional model represents the point cloud. Normal vector of one of the as point clouds essential attributes, its estimation method has important position in the point cloud processing. On the other hand, the noise is inevitable in the process to obtain because of the point cloud, error and occlusion, point cloud typically contains noise outside point and empty, and part of the sampling model such as CAD models, there will still be sharp features, which gave the normal vector estimated that presents a challenge. Overview of current existing point cloud normal vector estimation algorithm, analysis of the principle and key technologies, and analyzed their ability to deal with the noise, the outer points and sharp features and gives comparison, and finally provide some suggestions for future research)

％ 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)

通过M atlab 模拟了随机产生的一定概率分布的信号序列, 叠加高斯噪声后利用最大后验概率(MAP)检 测到的误码率, 做出BER~ SNR曲线, 并与理论计算得到的曲线进行比较, 两者吻合.(M atlab simulated by a certain probability distribution of random signal sequence, use of superposition of Gaussian noise is the maximum a posteriori (MAP) detection to the error rate, making BER ~ SNR curves obtained with the theoretical curve of the combined fit.)

量子遗传算法的源程序，很实用，很经典，适合入门 (Quantum genetic algorithm source code, very practical, very classic, suitable for entry)

说明：  基于rbf神经网络控制油船航行，对于学习神经网络控制的同志具有参考价值(based on neural network control tanker navigation, learning neural network control of the reference value of comrades)

复杂网络仿真及数据，matlab程序 电力网，公交网等电力网，公交网等(complex network)

gpc example for proyect

包括 基于MATLAB7.0 的NE（拉稀系数） RMSE MSE R2 等评价指标的计算编程程序(Including computing programming procedures of the NE, (diarrhea coefficient), RMSE, MSE and R2 .etc.based the MATLAB7.0)