firbp

How to use the ordinary Voronoi partition generator. The m-files also have their own help documentation that you can view in Matlab. This code creates a bounding polygon that is a square. Then it randomly creates 10 points and then creates and draws the partition. bounds = [0, 10, 10, 0 0, 0, 10, 10] points = 10 * rand(2, 10) regions = voronoi(bounds, points) drawRegions(bounds, regions) ================================ This is a brief set of instructions on how to use the Multiplicatively- weighted Voronoi partition generator. Each of the m-files has a help section, so in Matlab you can call: help mwvoronoi help drawRegions Here is an example that creates a bounding polygon, a square with side length 10. Then it randomly creates six points with random weights. Finally, the code draws the resulting partition. bounds = [0, 10, 10, 0 0, 0, 10, 10] points = 10 * rand(3, 6) regions = mwvoronoi(bounds, points) drawRegions(bounds, regions) Enjoy!

Raghuraj 与 Lakshminarayanan提出了基于特征值内相互关系建立预测模型,用于识别的模式识别方法——多变量预测识别模型（Variable Predictive Mode Based Class Discriminate, VPMCD）,并应用于生物学的模式识别中。VPMCD利用参数估计来建立预测模型，极大地减少了计算量，缩短了模型的训练时间。vpmcd5_revise为主函数，sec2_5_revise为训练函数(Variable Predictive Mode Based Class Discriminate, VPMCD)

基于最大信噪比的盲信号分离，采用MATLAB环境实现程序仿真(Maximum signal to noise ratio-based blind signal separation )

传统music算法，用于一个信号源的DOA估计，分辨力很好，很实用，可以用作初学者学习！(Traditional music algorithm, the DOA estimation for a signal source, the resolution is very good, very practical, can be used for beginners to learn!)

预测控制DMC算法，欢迎交流，简单明了。(programming for model-prediction control )

matlab入门级程序，对matlab基础仔细说明，比较简单(matlab entry-level program, the foundation is simple to use)

This function Compute the CIEDE2000 color-difference between the sample between a reference with CIELab coordinates Labsample and a standard with CIELab coordinates Labstd The function works on multiple standard and sample vectors too provided Labstd and Labsample are K x 3 matrices with samples and standard specification in corresponding rows of Labstd and Labsample The optional argument KLCH is a 1x3 vector containing the value of the parametric weighting factors kL, kC, and kH these default to 1 if KLCH is not specified.

用 matlab 编写的高斯随机表面的生成(using Matlab prepared by the surface of the Gaussian random generation)

asynchronous machine

雷达阵列天线的天线图，学习阵列信号处理可能会用得上(Radar array antenna of the antenna diagram, learning array signal processing may need them)