lec3

利用支持向量机完成的导航高度信息融合，需要用到lssvm toolbox。内的000是数据文件。(Support vector machine to complete a high degree of navigation information fusion, need to use lssvm toolbox. The 000 is the data file.)

Steerable高斯图像滤波器，非常不错 在国外网站上找到的，可以学习 (Steerable Gaussian filter images, very good abroad found on the site, we can learn from)

经过测试通过的floyd，matlab程序(Tested by the floyd, matlab program)

包络曲线的求法 matlab中的一种求上下包络的算法，特别经典的两种算法(Envelope curve for France matlab down in one envelope seeking algorithms, especially the classic two algorithms)

用matlab编程求解无约束优化问题、线性规划问题即在一组线性不等式或等式组的约束条件下求某个线性函数的最值问题(Matlab programming for solving unconstrained optimization problems, linear programming problems that most value problem for a linear function under the constraints of a set of linear inequalities or equations group)

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.

介绍一种有关卫星通信信号的快速盲检测方法(satellite communication signals quick blind detection)

这个是对16QAM各种界的一个整理，给出了仿真程序，对于初学者来说具有重要的意义。(This is a finishing 16QAM various circles, the simulation program, for beginners is of great significance.)

GA多目标优化的程序 带约束 里面有教程(GA multi-objective optimization program with constraints there are tutorials)

using RBF_NN intelligent architecture for the plant dynamic.