MATLAB

说明：  高斯噪声下的64QAM调制的误码率检测与理论值比较(Gaussian noise 64QAM modulation of the error detection rate compared with the theoretical value)

目标定位和跟踪的源程序，用于声目标的定位于跟踪 (target location and tracking of the source for acoustic target tracking in the positioning)

susan 开发源代码 在matlab 中的应用(susan code matlab)

Background Subtraction using Adaptive Gaussian Mixture Model

双向DC，plecs仿真，带闭环控制，可以联合仿真(Bidirectional DCplecs simulation)

一个关于人脸识别的pca主程序分析算法的matlab程序(About the pca a face recognition algorithm matlab main program analysis procedures)

A general technique for the recovery of signicant image features is presented. The technique is based on the mean shift algorithm, a simple nonparametric pro- cedure for estimating density gradients. Drawbacks of the current methods (including robust clustering) are avoided. Feature space of any nature can be processed, and as an example, color image segmentation is dis- cussed. The segmentation is completely autonomous, only its class is chosen by the user. Thus, the same program can produce a high quality edge image, or pro- vide, by extracting all the signicant colors, a prepro- cessor for content-based query systems. A 512  512 color image is analyzed in less than 10 seconds on a standard workstation. Gray level images are handled as color images having only the lightness coordinate(A general technique for the recovery of sig ni cannot image features is presented. The techni que is based on the mean shift algorithm, a simple nonparametric pro-cedure for estimat ing density gradients. Drawbacks of the curren t methods (including robust clustering) are av oided. Feature space of any nature can be proces sed, and as an example, color image segmentation is dis-cussed. The se gmentation is completely autonomous. only its class is chosen by the user. Thus, the same program can produce a high quality edge image, or pro-vide. by extracting all the signi cannot colors, a prepro- cessor for content-based query syste ms. A 512,512 color image is analyzed in less than 10 seconds on a standard workstation. Gray 4ISR l images are handled as color images having only the lightness c)

simple samples matlab(matlab easy introduction)

用MATLAB实现自适应神经模糊推理系统（ANFIS）结构训练。代码中，首先创建一个初始原ANFIS结构，然后采用遗传算法（GA）、粒子群优化（PSO）来训练ANFIS。此进化训练算法可用于解决非线性回归函数逼近问题。(Implementation of adaptive neural fuzzy inference system (ANFIS) based on MATLAB. Code, the first to create an initial original ANFIS structure, and then using the genetic algorithm (GA), particle swarm optimization (PSO) to train ANFIS. This evolutionary training algorithm can be used to solve the nonlinear regression function approximation problem.)

说明：  LMI编程实例，可行性问题，最优控制，次优化问题等求解(LMI programming examples, optimal control, etc)