改进WKNN

实验器材: 探索者STM32F4开发板 实验目的: 学习DS18B20数字温度传感器的使用. 硬件资源: 1,DS0(连接在PF9) 2,串口1(波特率:115200,PA9/PA10连接在板载USB转串口芯片CH340上面) 3,ALIENTEK 2.8/3.5/4.3/7寸TFTLCD模块(通过FSMC驱动,FSMC_NE4接LCD片选/A6接RS) 4,DS18B20传感器一个(接在PG9上). 实验现象: 本实验开机的时候先检测是否有DS18B20存在，如果没有，则提示错误。只有在检测到DS18B20之后才开始 读取温度并显示在LCD上，如果发现了DS18B20，则程序每隔100ms左右读取一次数据，并把温度显示在LCD 上。同样我们也是用DS0来指示程序正在运行。(Experimental equipment: Explorer STM32F4 development board Objective: Learn the use of DS18B20 digital temperature sensor. Hardware resources: 1, DS0 (connected to PF9) 2, serial port 1 (baud rate: 115200, PA9/PA10 connection on board USB to serial port chip CH340). 3 inch TFTLCD ALIENTEK, 2.8/3.5/4.3/7 module (via FSMC driver, FSMC_NE4 LCD chip select /A6 RS) 4, one of the DS18B20 sensors (attached to PG9). Experimental phenomena: This experiment first detects whether there is DS18B20 when starting up. If not, it prompts errors. Only after the detection of DS18B20 did it begin Read the temperature and display it on LCD. If DS18B20 is found, the program reads data once every 100ms or so and displays the temperature at LCD. On. Similarly, we also use DS0 to indicate that the program is running.)

说明：  GoDS (Go Data Structures). Containers (Sets, Lists, Stacks, Maps, Trees),

EasyD12动态连接库是Microsoft Windows的接口标准，流行的软件开发工具VC、VB、VF、Delphi、C++ Builder、Power Builder 等均可使用。用户可以选用自己喜爱的工具轻松搞定USB开发。其中包含2个版本DLL，根据情况自己选择。-EasyD12 dynamic link library is the Microsoft Windows interface standards, popular software development tools VC, VB, VF, Delphi, C Builder, Power Builder, etc. may be used. Users can choose their favorite tools easy to get USB development. Which contains two versions of DLL, according to the situation of their choice.

给于互相关的鲁棒的多通道的多声源DOA估计(multichannel source DOA estimation)

基于锁模光纤激光器的仿真，各器件已经模块化，可直接使用(Simulation of mode-locked fiber laser)

刷机专用软件，适合MOTO等大多数定制手机专用(Brush special software for MOTO customized mobile phones such as the majority of dedicated)

计算图像的一阶熵，二阶熵和差分熵，使用matlab编写，差分熵运行较慢(First-order calculation of image entropy, second-order entropy and differential entropy, using matlab write, the differential entropy is running slower)

说明：  多元经验模式分解（MEMD）算法是EMD算法从单个变量到任意数量的变量的扩展，其与经验模态分解一样存在模式混合问题，基于噪声辅助的多元经验模式分解（NAMEMD）就在对MEMD的改进，解决其问题。(The multiple empirical mode decomposition (MEMD) algorithm is an extension of the EMD algorithm from a single variable to any number of variables. Like the empirical mode decomposition, there is a mode mixing problem. The noise-assisted multiple empirical mode decomposition (NAMEMD) is just Improve and solve its problems.)

c语言经典例子导教，引导制作软件。入门必备(C language classic example guide, guide the production of software. Primer)

83_REALTEK8019as 芯片资料（中文）(83_REALTEK8019as chip data (Chinese))