ifix的OPC驱动程序，采用OPC通信的工程上可用。

PCI驱动开发框架-PCI driver development framework

使用OPCST开发的进程内OPCDA服务器(C++Builder)，利用OPCST工具包，可以在30分钟内开发出一个基本的OPCDA服务器。支持1.0和2.0。-use OPCST development process OPCDA server (C Builder), using OPCST kits in 30 minutes to develop a basic OPCDA server. Support 1.0 and 2.0.

MPLABC18 V3.10 Compiler. Compile C program for Microchip chipset

firewire cam corder.

c#版自动升级代码,2005编写的 c#版自动升级代码,2005编写的-c# version of automatic upgrade code, 2005, prepared by auto-upgrade version of c# code, 2005, prepared by auto-upgrade version of c# code, 2005, prepared

您的文件包然后写出其具体功能(至少要20个字)。尽量不要让站长把时间都花费在为您修正说明上。压缩-Your package and then write their specific functions (at least 20 words). Try not to let the station master at the time you spend on the amendment note. Compression

TW2834的驱动程序设计。包括各个寄存器标准值设计。对于理解TW2834与ITU656非常有帮助-TW2834 driver design. Standard values in all registers, including the design. For understanding the TW2834 with ITU656 very helpful

驱动程序超级宝典，这个可是中文版本的，绝对值得收藏！-book, but the Chinese version, and definitely worth collecting!

YSS915 (KP2V2) is an LSI for processing Karaoke voice signals. This LSI has an A/D converter (1 channel) for the microphone echo, and a memory for the microphone echo and key control. These features allow achieving the functions needed for the Karaoke system by using only one LSI chip. As for the microphone echoes, many other types of echoes are available in addition to ordinary ones so that YSS915 is applicable to various uses. In addition to these Karaoke programs, YSS915 is able to provide the Movie & Music programs, with which the surround effect is applied to the movie and music sources for giving the users more enjoyment. YSS915 is pin compatible with and register compatible with YSS903 (KP2V).-YSS915 (KP2V2) is an LSI for processing Kar aoke voice signals. This LSI has an A/D converte r (a channel) for the microphone echo, and a memory for the microphone echo and key cont rol. These features allow achieving the functi ons needed for the Karaoke system by using only

Learning Bayesian NetworksWith Hidden Variables for User Modeling