MA6

Motion Tracking =============== This tarball contains all code required to run the tracking algorithm on a sequence of images. Run the file run_tracker.m in Matlab and follow the instructions. You will need to have a directory of sequentially numbered images available. After entering the path and file types the tracker will begin processing. Once the data window appears the algorithm begins building a background model and attempts to track objects. By clicking on any of the four subwindows you can investigate the background representation (a Mixture of Gaussians) of any pixel. The two windows that then appear display the mixture once as a two-dimensional scatter plot (ignoring the blue colour component), and once as a one-dimensional evolution of the red colour component only. These plots make the internal processing visible and should help determining suitable parameters to be set in mixture_parameters.m.

THIS IS ABOUT MATLAB IMAGE BINARIZATION

Structures Theory in Spanish.

Matlab program for railway abnormal detection and imaging,including GUI, open dlg, processing dlg and source code.

实用的小波包分析程序，用于信号的等频段分解。(very usefull wavepack code, for signal decomposition with equal frequency band.)

matlab在通信原理中的应用，信道编码BCH码仿真，希望大家能用得上！(matlab in Communication Theory in the application of channel coding BCH code simulation, hope that we can useful!)

real time implementation for video tracking based on color using particle filter in matlab

MOdel to control dcM

RNA 和 DNA序列模拟 基因建模 数值模拟 采用matlab 编写 能计算几千个 基因点的特性和行为(In one type of gene expression analysis, fluorescently tagged messenger RNA from different cells are hybridized to a microscopic array of thousands of complimentary DNA spots that correspond to different genes. Illuminated spots emit different color light, indicating which genes are expressed (e.g., green=control, red=sample, yellow=both). In this case study, MATLAB, the Image Processing and Signal Processing toolboxes were used to determine the green intensities from a small portion of a microarray image containing 4,800 spots. A 10x10 pattern of spots was detected by averaging rows and columns to produce horizontal and vertical profiles. Periodicity was determined automatically by autocorrelation and used to form an optimal length filter for morphological background removal. A rectangular grid of bounding boxes was defined. Each spot was individually addressed and segmented by thresholding to form a mask. The mask was used to isolate each spot from surrounding background. Individu)

本程序利用m文件对车体的自振频率进行了求解，(natural frequency of the body)