matlab源程序

MABLAB中模糊逻辑工具箱的使用实例源代码(The use of fuzzy logic toolbox)

some genetic algorithmes

End POint detection algorithm using Energy-ZCR

spring document very mush

简单pid和串级pid的matlab仿真(Simple cascade pid pid and the matlab simulation)

详细介绍了MATLAB与控制工程相关的6个基础工具箱：系统辨识工具箱、控 制系统工具箱、鲁棒控制工具箱、模型预测控制工具箱、模糊逻辑工具箱和非线性控制设计模块。同时提供了MATLAB的一些基础知识。(Details related to MATLAB and Control Engineering of the six basic kit: System Identification Toolbox, Control System Toolbox, Robust Control Toolbox, Model Predictive Control Toolbox, Fuzzy Logic Toolbox and nonlinear control design module. Also provides some basic knowledge of MATLAB.)

Matlab 图片拼接 包内是.m文件，注意图片命名，需要手动配置修改(Matlab image stitching package is.M files, note that the picture naming, the need for manual configuration changes)

在基于前景检测的基于移动物体检测和车辆跟踪算法的实现中，针对广泛的应用来实现读取AVI文件，并将其分解为R，G和B组件。 执行各种操作并检测移动物体。 各个阶段的阈值决定了识别某些尺寸的移动物体的可能性。 移动物体也在其中跟踪。 MATLAB用于实现算法。 该算法用包含120帧的输入avi格式视频文件进行测试。 研究并实现了这些算法的各种应用。(In this foreground detection based moving object detection and vehicle tracking algorithm is implemented targeting a wide class of applications. An AVI file is read and it is decomposed into R, G and B components. Various operations are carried out and the moving objects are detected. Thresholds at various phases are decide the possibility of identifying the moving object of certain sizes. Moving objects also tracked in it. MATLAB is used for implementation of the algorithm. The algorithm is tested with input avi format video files consisting of 120 frames. Various applications of these algorithms are studied and implemented. Main focus is given on (unmanned aerial vehicle) UAV based and automatic traffic estimation applications)

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)) )

辐射边界和定温边界条件下，二维矩形平板的温度场数值模拟。(Radiation boundary and constant temperature boundary conditions, two-dimensional rectangular plate temperature field numerical simulation.)