基于模板匹配的手写模式识别

matlab从入门到精通全书源代码，希望对大家有用(matlab book from entry to the master source code, useful for all of us hope)

说明：  系统地介绍了模糊控制在自动发电机控制中的应用，并对控制结果进行了详细地分析与介绍。(a systematic introduction to fuzzy control in automatic generator control applications, results of control for a detailed analysis and briefings.)

说明：  NOMA仿真，能够实现两用户的NOMA系统仿真的实现，对于初入NOMA者非常有用(NOMA simulation, which can realize the simulation of two-user NOMA system, is very useful for new entrants to NOMA.)

说明：  卡尔曼滤波相关代码，内含线性卡尔曼，扩展卡尔曼，无迹卡尔曼，交互多模型卡尔曼的代码(Kalman filter related code, including linear Kalman, extended Kalman, unscented Kalman, interactive multi model Kalman code)

matlab高斯滤波、中值滤波、均值滤波.rar-Three mathod of matlab filtration

二进制粒子群优化算法pso，主程序：swarmpso.m 它包括以下子程序： 1.　初始化：swarminit.m 2.　适应值计算函数：swarmeval.m； (Binary particle swarm optimization pso, the main program: swarmpso.m It includes the following subroutines: 1. Initialized: swarminit.m2. Adaptation value function: swarmeval.m )

Local Standradr Deviation Image Enhancment for a batch of files or several slices.

位置指令为幅值为1.0的阶跃信号，r（k）=1.0。网络结构为1-4-1，高斯函数的参数值取Cj=[-2 -1 1 2]T ，B=[0.5 0.5 0.5 0.5]T 。 网络权值学习参数为η=0.30，α=0.05 。PID控制各参数的初RBF网络控制，被控对象为G（s）= 取采样时间为1ms，采用Z变换进行离散化，离散化后的被控对象为 y(k)=-den(2)*y（k-1）-den(3)*y(k-2)+num(2)*u(k-1)+num(3)*u(k-2) 始值为，kp=20， kd=0.3， ki=0.1。 (Position command for the step signal amplitude of 1.0, r (k) = 1.0. The network structure is 1-4-1, the Gaussian function parameters taken Cj = [-2-1 1 2] T, B = [0.5 0.5 0.5 0.5] T. Weight learning parameter η = 0.30, α = 0.05. PID control parameters at the beginning of each RBF network control, the controlled object is G (s) = take the sampling time is 1ms, using the Z transform discrete, discretized controlled object is y (k) =-den (2)* y (k-1)-den (3)* y (k-2)+num (2)* u (k-1)+num (3)* u (k-2) initial value, kp = 20, kd = 0.3, ki = 0.1.)

这是我图像处理作业：图片曲线数据提取与峰值检测的源程序代码。(Peak detection program matlab code)

主要是用来K均值聚类，K值按照自己的需要设置并将聚类结果保存到相应目录下的excel文档中(Mainly used K-means clustering, K value is set according to their needs and clustering results are saved to the appropriate directory under the excel document)