nengqeng

本文件含有关于matlab学习的资料，适用于初学者(This document contains information on learning matlab for beginners)

The files explain aliasing , gibbs, dft and fft. All are very useful in signal processing applications and the files illustrate the contents very well with plots/graphs.

该函数的功能是利用matlab实现图像的快速有效的分割(Function of the function is to use matlab to achieve fast and efficient image segmentation)

描述matlab的面向对象编程的一些原则(Describe some of the principles of the Matlab object-oriented programming)

对模型参考自适应进行仿真，并且给出控制算法的改进(The model reference adaptive simulation, and gives the control algorithm )

Ingrid Daubechies《小波十讲》(中文版)具体电子数目及应用(Ingrid Daubechies, "Ten Lectures on Wavelets" (Chinese version), the number of electrons and)

如何使用matpower,方便易懂，值得学习(How to use the MATPOWER, easy to understand, it is worth learning)

1.IMM.m 主要功能： （1）IMM算法的实现； （2）画出目标轨迹与利用IMM算法跟踪目标的轨迹； （3）画出位置误差与速度误差； （4）画出模型混合概率图。 2.Target_track.m 主要功能： 实现目标轨迹的产生。 3.Model_mix.m 主要功能： 实现IMM算法下，各模型的估计融合。 4.Kalman.m 主要功能： 实现模型的条件滤波，以及似然函数的输出。(1.IMM.m main functions: (1) IMM algorithm implementation (2) Draw the locus and utilization of IMM target tracking algorithm goals (3) shows the position error and speed error Mixed (4) Draw model probability plots. 2.Target_track.m main functions: to produce the target locus. 3.Model_mix.m main functions: IMM algorithm, it is estimated each model integration. 4.Kalman.m main functions: the model filter condition, and it seems natural function of the output.)

LMS算法实现自适应滤波 clear close all clc N=10000 设置仿真长度 信号产生参数设定 a1=-0.195 a1=-1.5955 a2=0.95 R0=[1,a1,a2 a1,1+a2,0 a2,a1,1] p=[1,0,0] r=inv(R0)*p 计算理论自相关函数 R=[r(1),r(2) r(2),r(1)] 生成理论自相关矩阵 p1=[r(2),r(3)] 生成互相关 h=inv(R)*p1 计算维纳解 Jmin=r(1)-h *p1 计算维纳解时最小均方误差 u=1/sum(eigs(R)) ( LMS算法实现自适应滤波 clear close all clc N=10000 设置仿真长度 信号产生参数设定 a1=-0.195 a1=-1.5955 a2=0.95 R0=[1,a1,a2 a1,1+a2,0 a2,a1,1] p=[1,0,0] r=inv(R0)*p 计算理论自相关函数 R=[r(1),r(2) r(2),r(1)] 生成理论自相关矩阵 p1=[r(2),r(3)] 生成互相关 h=inv(R)*p1 计算维纳解 Jmin=r(1)-h*p1 计算维纳解时最小均方误差 u=1/sum(eigs(R)) )

the above uploaded codes are very useful for image segmentation,edge detection