xianxingtiaopin

二进制编码GA求Rosenbrock函数极大值(The binary coded GA Rosenbrock function maxima)

bp神经网络matlab实现和matlab工具箱使用实例(bp neural network matlab matlab toolbox and use cases to achieve )

包含优化类的几个简单示例程序，matlab程序运行时导入数据文件作为输入参数，多姿态，多角度，有不同光照,研究生时的现代信号处理的作业，计算多重分形非趋势波动分析。( Optimization class contains several simple sample programs, Import data files as input parameters matlab program is running, Much posture, multi-angle, have different light, Modern signal processing jobs when the graduate, Calculate the multifractal trend fluctuation analysis.)

脊波工具和相关实验以及有关实验数据，对实现脊波应用有着相当重要的源码(Ridgelet tools and related experiments and the experimental data, the application of the realization of ridgelet have very important source)

一个运用Matlab仿真工具，结合机械臂运动学特性，实现了机械臂系统的运动学仿真。(Using a Matlab simulation tools, combined with the arm kinematics, kinematic manipulator system to achieve a simulation.)

it is histogram matching using companding method

Code to find a word that fit to mask.

滤波器实例，matlab的，学完动态信号分析的作业，华南理工大学研究生课程(Filter instance, matlab, completion of the job of the dynamic signal analyzer, South China University of Technology postgraduate courses)

Energy-efficient Deployment of Mobile Sensor Networks by PSO

多变量输入、输出、多干扰、非线性和强耦合的复杂系统控制是一个比较困难的问题，常用的控制器可能因为多变量耦合问题难以控制系统。PID神经元网络是一种多层前向神经元网络，它的各层神经元个数、连接方式、连接权值是按照PID控制规律的已有原则和经验确定的，是一种动态的符合控制系统的前向网络。但是由于PID网络初始权值随机取值的原因，每次控制的效果都有所差别，个别情况下控制效果还比较差。本案例研究了基于PID神经元的多变量耦合系统控制，并用PSO算法来优化控制器以取得更好的控制效果。(Multivariable input, output, and more interference, complex nonlinear and strong coupling system control is a more difficult problem, commonly used multivariable controller may be because the problem is difficult to control the coupling system. PID neural network is a multi-front to neural networks, its number of neurons in each layer, connection, connection weights are in accordance with the existing principles and experience to determine the PID control law is a dynamic compliance before the control system to the network. However, due to the random initial weights of the network PID values ​ ​ of reason, every time there are differences in the effect of control and in some cases the control effect is still relatively poor. This case study of multivariable coupling system based on PID control neurons, and with PSO algorithm to optimize the controller to achieve better control effect.)