bellman_1

高通滤波器实现，可用于小目标检测，效果还不错，对于初学者很有帮助(High-pass filter can be used for small target detection, the results were good, very helpful for beginners)

It is a particle filter tracker implemented in Matlab.

该文件中包含了详细的matlab实现的源代码，很适合初学者入门。代码的运行环境有要求： 1. 软件环境 需要安装暴风影音才能正常播放.WMV文件； MATLAB R2011b 版本的软件。 2. 硬件环境 处理器：CPU主频不低于1GHz； 内存：不小于256MB； 硬盘：不小于10GB； 显示器：支持1024*768分辨率。(The file contains a detailed matlab realize the source code, it is suitable for beginners. Operating environment code required: 1 Software Environment         STORM need to be installed in order to play properly .WMV file         MATLAB R2011b version of the software.     2 hardware environment         Processor: CPU clock speed of not less than 1GHz         Memory: not less than 256MB         Hard disk: not less than 10GB         Display: 1024* 768 resolution.)

基于matlab的图像处理技术，可以对bmp，jpg等格式的图片进行处理，可以反转(Image processing technology based on MATLAB, on BMP, JPG format image processing, can be reversed)

独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S + N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...( Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S+ N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...)

张正友标定法工具箱,进行了相应的优化，参考ICTIS2015论文(zhang s calibration lib tools)

说明：  例程，用于功能测试。如程序有错请大家指出.(Routine for function testing. If there is any mistake in the procedure, please point out)

Setup the Raspberry Pi to work with Matlab. Check out the Matlab Hardware Support Package documentation. This GUI based program will automatically connect to the Raspberry Pi if already configured. It shows the Pin logic values in color. The Pin headers P1 and P5 are shown exactly as on the Raspberry Pi. Additionally, it shows the actual location of the Pin Header on the Raspberry Pi. Pin direction can be set to INPUT or OUTPUT by clicking on the side buttons. Directly clicking on the Pins will change the status on the Raspberry Pi. Pin statuses are shown live. NB: This program won t work with new Raspberry Pi Model B+.

IS95前向链路系统的性能仿真,通过MATLAB进行建模，得出仿真结果(The simulation of IS95 forward link system performance )

建立模型参考自适应系统(MRAS)来估计转子磁链，最后通过Matlab／Simulink仿真与基于DSP的无速度传感器异步电动机矢量控制实验(Model reference adaptive system (MRAS) to estimate the rotor flux, and finally through Matlab/Simulink Simulation and DSP-based induction motor speed sensorless vector control experiments)