PCA

计算傅立叶光学的实现，可以用于GS算法（需要改造），角谱算法的参考，基础算法本人已经验证，可实现衍射的计算，经开发可以用于DOE（衍射光学元件）的设计(The realization of computational Fourier optics can be used as a reference for GS algorithm and angular spectrum algorithm. The basic algorithm has been verified by myself, and can be used for the calculation of diffraction. The developed algorithm can be used for the design of DOE (Diffractive Optical Element).)

各种门电路模型的VerilogHDL描述-various gates model of Verilog HDL description

dali灯光（一个时间灯光控制标准）协议通讯函数库(Dali light protocol communication function library)

说明：  一个练习打字的游戏，字母下落，恩与字母相同的键就可以大落字母。(a practice typing games, in alphabetical whereabouts TU with the same letters on the keys can drop large letters.)

1、包含GVF Snake和CGVF Snake的Matlab工具包 2、调用工具包内各函数完成GVF Snake和CGVF Snake的完整示例代码及其注释 3、附梯度矢量流英译汉注释文献(1. Matlab Toolkit with GVF Snake and CVF Snake 2. Call the functions in the toolkit to complete the sample code of GVF Snake and CVF Snake (annotated) 3. English-Chinese Translation of Annotated Documents with Gradient Vector Stream)

说明：  tcmsp爬虫，医学相关，python开发，带操作界面，使用tkinter开发(Tcmsp crawler, medical related, Python development, with GUI by Tkinter)

说明：  体温检测仪：实验先计算出人体体温从44℃----30℃的ADC口值 ，再用查表法进行比较，计算，就得出温度值，再显示出来。(Body Temperature Detector: The experiment first calculates the ADC value of human body temperature from 44 to 30 C, and then compares it with the look-up table method, calculates the temperature value, and then displays it.)

通过加截特殊字符，自定义LED字体效果，内附LED字体文件，可直接运行(Custom LED font effect)

说明：  trubo code with sova algoritm in matlab

说明：  SLIC算法是simple linear iterative cluster的简称，该算法用来生成超像素（superpixel） 算法步骤： 已知一副图像大小M*N,可以从RGB空间转换为LAB空间，LAB颜色空间表现的颜色更全面 假如预定义参数K，K为预生成的超像素数量，即预计将M*N大小的图像(像素数目即为M*N)分隔为K个超像素块，每个超像素块范围大小包含[（M*N）/K]个像素 假设每个超像素区域长和宽都均匀分布的话，那么每个超像素块的长和宽均可定义为S，S=sqrt(M*N/K) 遍历操作，将每个像素块的中心点的坐标(x,y)及其lab的值保存起来，加入到事先定义好的集合中(Algorithmic steps: Given the size of an image M*N, it can be converted from RGB space to LAB space, and the color space of LAB is more comprehensive. If the predefined parameter K, K is the number of pre-generated super-pixels, i.e., the image of M*N size (the number of pixels is M*N) is expected to be divided into K super-pixel blocks, each of which contains [(M*N)/K] pixels. Assuming that the length and width of each super-pixel region are evenly distributed, the length and width of each super-pixel block can be defined as S, S = sqrt (M*N/K). The traversal operation saves the coordinates (x, y) and lab values of the central points of each pixel block and adds them to a pre-defined set.)