zhendongwentideyouxianyuan

锁相环的matlab simulink 仿真(The objectives of this laboratory are: To introduce students to Phase Locked Loops (PLL) and their operation. To predict and measure the PLL characteristics. To set up practical circuits using the PLL.)

Base paper is regarding robust face recognition

一款利用matlab编写的射线追踪程序，易改易用。(The installation of TTBOX is relatively simple. All you have to do is to create some directories and tell MatLab, where TTBOX is. if it does not already exist, create a directory matlab within your home directory. Copy the TTBOX directory into the matlab directory if it does not already exist, create a file startup.m within the matlab directory Insert the following lines into startup.m: basepath= This should be the path to your home directory! addpath([basepath filesep matlab filesep ttbox ],1) addpath([basepath filesep matlab filesep ttbox filesep support ],1) execute startup within the MatLab command window. MatLab is now ready to execute TTBOX routines. The startup-script will be executed automatically upon start of MatLab. In order to read the online documentation, you have to browse to the doc directory and open the ttbox/doc/ttbox.html file with your web browser (it is recommended to set a bookma)

Adaptive filter using Matlab

实现Pisarenko谐波分解法、MUSIC、基本ESPRIT、LS-ESPRIT、TLS-ESPRIT五种频率估计算法，并运用之对一个正弦波叠加噪声的信号源进行频率估计。(Use methods of Pisarenko, MUSIC, ESPRIT, LS-ESPRIT and TLS-ESPRIT to do frequency uation of one signal, which is composed of 3 sine waves and 1 white noise.)

correcteur pid p pi némurique

基于matlab开发的协整套利策略测试模型(matlab cointegration arbitrage )

汽车动力学分析程序.车辆.航空和能动工程方面的同志可以参考,也可以作为Matlab GUI编程的经典范例(Vehicle dynamics analysis program. Vehicles. Airways and dynamic engineering comrades can refer, but also can be used as a classic example of Matlab GUI programming)

a third ameliorate version of DSPview code in matlab

利用matlab对随机过程课程的仿真 1、利用matlab绘制随机过程的谱密度G_x (ω)=2αβ/(β^2+ω^2 ) (α、β为正数)的图像。 2、绘制白噪声的功率谱密度函数G_x (ω)=N/2和自相关函数R_N (τ)=N/2 δ(τ)的图像。 3、分析低通白噪声和带通白噪声的功率谱密度函数和自相关函数的性质并举例同时绘制其图像。 (1, drawn using a random process matlab spectral density G_x (ω) = 2αβ/(β ^ 2+ ω ^ 2) (α, β positive) image. 2 for the white noise power spectral density function G_x (ω) = N/2 and the autocorrelation function R_N (τ) = N/2 δ (τ) of the image. 3, the analysis of low-pass white noise and band-pass white noise power spectral density function and autocorrelation function of the nature and the examples at the same time to draw its graphics.)