QPSK

这是一个粒子群算法（PSO）用于特征选择的matlab函数，用户可以自由选择目标函数优化方向、种群大小、迭代次数等等。(this is an feature selection program with particle swarm optimization of matlab ,you can chose the Function optimization direction the scale of the swarm and the number of the iteration)

ISAR simulation on ISAR motion compensation and SAR imaging Matlab source

首先在m脚本文件canshuo.m中输入节点个数和路径权重，在命令窗口中输入canshu，用s=12,e=10的格式输入要求的起止点，再输入main即可得到两点之间的路径和长度。(M script file canshuo.m first enter the node number and the right path lies in the command window enter canshu, with s = 12, e = 10 The format of the input requirements of the start and end points, and then enter the main between two points can be obtained path and length.)

MATLAB信号处理详解,陈亚勇著，丰富的源码(Detailed MATLAB signal processing, Chen Yayong book, a rich source)

file contains file contains matlab program matlab program file contains matlab program

local binery (lbp), feature extraction for target tracking applications

《MATLAB控制系统仿真与实例详解》一书的光盘源码。图书简介：本书详细地讲解了MATLAB 7.x的功能与相关操作以及MATLAB在控制系统中的仿真应用。本书内容包括控制系统仿真基础、MATLAB程序设计语言基础、控制系统理论基础、Simulink交互式仿真环境、控制系统建模、线性控制系统的分析与仿真、PID控制系统设计及仿真、最优控制系统设计、鲁棒控制系统设计、神经网络系统设计及其MATLAB实现、模糊控制系统设计和系统辨识。 (" MATLAB Control System Simulation and explain examples of" one-source book on CD-ROM. Book Description: This book explain in detail the function of the MATLAB 7.x and related operations and MATLAB in the control system simulation applications. The book includes basic control system simulation, MATLAB programming language basic, basic control system theory, Simulink interactive simulation environment, control system modeling, linear control system analysis and simulation, PID control system design and simulation, optimal control system design, robust control system design, neural network system design and MATLAB implementation, fuzzy control system design and system identification.)

一个学习matlab的课件，对于新入门的学习者比较有帮助(Matlab a learning courseware, the new entry for more helpful to learners)

Simulated annealing using the Metropolis criterion for TSP

Differential Evolution with DEoptim