MATLAB_M

说明：  vhdl 初学例程，对于初学者有很大的参考价值哦(VHDL beginner routines for beginners have great reference value oh)

说明：  1.1 背包问题 有一个徒步旅行者，已知他能承受的旅行背包的重量不超过a（kg）。设有n种物品可供他选择装入背包，这n种物品分别编号为1，2，…，n。其中第i种物品每件的重量为ai（kg），其使用价值（指一件第i种物品对旅行者来说所带来的好处的一种数量指标）为ci（i＝1，2，…，n）。问这位旅行者应如何选择携带这n种物品的件数，使得总价值最大？ (1.1 knapsack problem is a hikers. he is known to travel to withstand the weight of the backpack not exceed a (kg). N Species with articles for his choice loaded backpack, n product were numbered 1, 2, ..., n. I first of which product each ai of the weight (kg), its value (i refers to a section of the types of items travelers the benefits brought by a number of indicators) for the ci (i = 1, 2, ..., n). Asked how travelers who choose to bring this product to the n pieces, making the total value of the largest?)

基于牟老师的关于三层光纤的SPR反射率计算公式的图像处理部分，自己设计的，随波长变化反射率变化曲线(The formula based on Mou teacher SPR reflectance of about three fiber optic image processing section of their own design, varies with wavelength reflectance curve)

一个参照葛德彪书编写的3D FDTD源文件，用matlab语言编写，非常详细的注释，很易看懂,2mur bianjie(GE De-biao a reference book, prepared by 3D FDTD source files, using matlab language, very detailed notes, it is easy to understand, 2mur bianjie)

有需要的自己下载查看 内部有图有程序 (There is a need to download the view of its own internal procedures have plans has)

说明：  通过输入一个有权图，求出它的最短的一条哈密顿回路。(By entering a right map, obtained with a shortest Hamiltonian circuit.)

关于matlab语言与控制系统设计方面的一些例子(Some examples of the the matlab language with control system design)

说明：  matlab编写的相同要求时提某列取大小值。(Matlab prepared by the same requirements when a series from a size value.)

滤波器实例，matlab的，学完动态信号分析的作业，华南理工大学研究生课程(Filter instance, matlab, completion of the job of the dynamic signal analyzer, South China University of Technology postgraduate courses)

Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for the k-fold cross-validation of SVR. All the programs are flexible and could be implemented by the users themselves.