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- 在S3C44B0X的学习板上实现UCOS的移植，成功控制3个发光二极管-To achieve the learning panel at S3C44B0X UCOS transplant, successful control of three light-emitting diodes
Mboxled
- 采用proteus7.7来仿真基于ARM和UcosII的一个学习范例，通过邮箱来控制led闪烁。-Used to simulate proteus UcosII based ARM and a learning example to control the led flashes through the mail.
Buzzer-control
- 这是一个蜂鸣器控制的实验，学嵌入式的朋友可以看看。-This is a buzzer-controlled experiments, learning embedded friends can see.
tankcode
- ucos控制项目的全部代码, 可以编译运行， 是ucos应用开发进阶好代码。-codes for a ucos control project, can be compiled and run, good for learning ucos application development
ARMDesign
- ARM实现交通灯控制系统，对于学习UCos嵌入式实习操作系统有一定的帮助-ARM traffic light control system for learning UCos embedded practice operating system will certainly help
ucos-sound
- 2410下的ucos系统音频控制实验，系统移植了完善的文件功能， 是学习嵌入式操作系统非常好的例子。-The ucos under the 2410 system audio control experiments, system migration file is learning embedded operating system is a very good example.
lm3S
- 针对LM3S系列单片机的ucos的源码，共有10个例程，资源丰富，涉及的内容有基本的IO控制，多任务的编程学习-Source for the ucos of LM3S series microcontroller, a total of 10 routines, rich in resources, involving the contents of a basic IO control, multi-task programming learning
uTenux
- µ Tenux嵌入式实时操作系统是基于日本T-Kernel开发而来，从2009年发布升级至今。上传版本为V1.6版本。 1、现在已经支持IAR、Keil、eclipse+gcc三个环境。 2、主要支持ARM7/9、全线支持Cortex-M0、3、4的ARM内核芯片 3、支持CMSIS 4、只要应用医疗电子、工业控制、办公电子等 5、uTenux学习讨论群：218329305（CSDN推荐）-μTenux embedde
DMAPPID
- 电动汽车平衡 算法（包括姿态算法，电机控制算法），是一种很好的学习资料。-The electric car balance balance algorithm (including attitude algorithm, motor control algorithm), is a good learning materials.
leng_gj78
- Mutual information is useful to calculate a set of procedures, Acquisition and Processing of the speech signal, digital signal processing class-based, Linear array using cut than learning laid upon the right control of the main sidelobe ratio.
ie471
- Linear array using cut than learning laid upon the right control of the main sidelobe ratio, Complete class-based image processing, contains all of the source code, auto image, Contains the eigenvalue and eigenvector extraction, the training sample,