Mobile application development is the development of applications on mobile appl...

bittorrent source by python. please enjoy-bittorrent source by python. Please enjoy

完整的usb massstorage 的协议文档-Usb massstorage complete agreement document

掌握CSS：高级网络标准解决方案 这个是英文版。-master CSS : Senior Network Solutions standards this is the English version.

有用systemview进行仿真的朋友，这里面是用systemview开发的仿真例程，相当棒！不看看，可惜啊，我的硕士论文就靠他了！-useful Systemview simulation friends, There is Systemview development of the simulation routines, rather wand! Not see, but ah, my master"s thesis depends on him!

支持串并行接口的12864，主控为ST7920A，还有源码参考。 DI EQU P3.7 E EQU P3.5 RST EQU P3.2 cs1 equ p3.0 cs2 equ p3.1 ;本测试程序中CS1,CS2=H ,RW =>GND ORG 0000H LJMP MAIN ORG 0003H LJMP LINTO ORG 0100H MAIN: NOP clr ea clr cs1 clr cs2 CLR E lcall init MOV 34H,#0ffH LCALL DISPLAY_ALL lcall dly100 MOV 34H,#00H LCALL DISPLAY_ALL lcall plybw lcall DLY100 MOV 34H,#00H LCALL DISPLAY_ALL MOV R1,#0C0H ;START = 0 LCALL WRI mov 31h,#0 mov 30h,#0 MOV 30H,#0 ;x MOV 31H,#8 ;y MOV DPTR,#HZI7 ;您 LCALL outhz MOV 30H,#0 MOV 31H,#40 MOV DPTR,#HZI8 ;好 LCALL outhz MOV 30H,#4 MOV 31H,#16 MOV DPTR,#HZI1 ;* LCALL outhz MOV 30H,#4 MOV 31H,#32 MOV DPTR,#HZI2 ;* LCALL outhz MOV 30H,#6 MOV 31H,#0 MOV DPTR,#HZI3 ;电 LCALL outhz MOV 30H,#6 MOV 31H,#16 MOV DPTR,#HZI4 ;子 LCALL outhz MOV 30H,#6 MOV 31H,#32 MOV DPTR,#HZI5 ;公 LCALL outhz MOV 30H,#6 MOV 31H,#48 MOV DPTR,#HZI6 ;司 LCALL outhz LCAL

是一个java的反编译工具软件，可以很好的对java的class文件进行反编译-Is a tool to decompile the java software, can be very good for the class file java decompile

一篇有关编译原理的讲义，我认为讲得还是比较详细的，适合初学者-a compiler of the principle of lectures, I think or speak in more detail, see for beginners

matlab6.5的设计细则，很有用呦。我看了写的还蛮详细的。大家一定要挺呀。-matlab6.5 design rules, very useful Yo. I have read quite a detailed written. Rather it must be everybody.

视觉基本.NET优秀编程源码第七章100个案例

：介绍了扩展卡尔曼滤波算法和无迹变换(unscented transformation，UT)算法，并对扩展卡尔曼滤波算法(EKF)和无 迹卡尔曼滤波算法(UKF)进行比较，阐明了UKF优于EKF。在此基础上，提出了一种基于Unscented变换(uT)的高斯和滤 波算法，该算法首先通过合并准则得到适当个数的混合高斯模型，逼近系统中非高斯噪声的概率密度-: Introduction of the extended Kalman filter algorithm and unscented transform (unscented transformation, UT) algorithm, the extended Kalman filter algorithm (EKF) and unscented Kalman filter (UKF) for comparison to clarify the UKF is superior to EKF. On this basis, we propose an approach based on Unscented Transform (uT) and the Gaussian filtering algorithm, which first of all, by merging the appropriate number of criteria to be a mixture of Gaussian model, which was close to the system of the Central African Gaussian noise probability density