MATLAB

说明：  一片详细介绍adaboost进行目标识别的文章。采用MSTAR数据库作为数据来源，非常经典的adaboost实现(A detailed article adaboost target recognition. MSTAR database as the data source used, to achieve a very classic adaboost)

matlab code to transform RGB into HCV

Research paper on Power Line interference noise removal techniques from ECG signal. It is a technical paper that reviewed on different methods used.

此算法用于多目标优化，是经过修改的，可以运行！(This algorithm is used for multi-objective optimization 。 Modified, you can run!)

利用matlab实现相干信号的music算法，DOA估计相干信号的music算法(Using matlab to achieve a coherent signal of the music algorithm, DOA estimation of coherent signals of the music algorithm)

衰减记忆滤波算法,通过对原信号的滤波从而得到一阶、二阶信号导数的估计值(fading memory filter)

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!

《MATLAB7.0编程基础》书中图形的源代码，这是第5章的集合，比较全面，很有用，是很好的参考。(" Matlab7.0 programming foundation graphics source code in the book, which is a collection of Chapter 5, more comprehensive, useful, is a good reference.)

研究目标跟踪的状态估计方法，最小二乘估计，Kalman滤波，扩展Kalman滤波，无迹Kalman滤波以及粒子滤波等，理论及MATLAB源程序。(The state estimation methods of target tracking, least square estimation, Kalman filtering, extended Kalman filtering, unscented Kalman filtering and particle filtering, theory and MATLAB source program are studied.)

通过粒子群算法快速解决旅行商问题,其中还可以自己设置参数，学习因子，惯性权重等。(Through particle swarm algorithm quickly solve traveling salesman problem, which can still parameters, the learning factor, self-adapting inertia, etc. )