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微软 Dynamics AX2012财务操作手册(Microsoft Dynamics AX2012 Financial Manual)

详细分析了windows环境下PATH环境变量的配置方法，为程序的安装提供修改路径的前提。(Detailed analysis of the configuration of the PATH environment variable in windows environment, modify the path of the premise for the installation.)

oracle 11g数据库安装图解说明，非常实用！！(oracle 11g install example)

包含所有informatica powercenter的错误信息以及排错方法(Contains all the informatica powercenter error messages and troubleshooting techniques)

Linux虚拟机NAT网络连接设置，介绍各种连接方法，以及可能出现各种问题的解决办法。(Linux Virtual Machine NAT network connection settings, and introduce a variety of connection methods, and the possible emergence of a variety of solutions to the problems.)

对计算机中使用的总线比较详细的介绍和总结,希望对大家有用(On the computer bus used in a more detailed introduction and conclusion, we wish to be useful)

LoadRunner 11.0安装详细手册(LoadRunner 11.0 Installation detailed manual)

GNOME和KDE桌面的管理 包括简单的桌面管理，系统的时间＆日期设置、挂载软盘、光盘和U盘，控制中心，添加删除应用程序，打印机的安装与设置等(GNOME and KDE desktop management Including simple desktop management, system of time and date on the set, floppy diskettes, optical disks and U disk, the control center, add or remove applications, printer installation and setting, etc )

Java MyEclipse作为IDE的Java开发环境的基本搭建过程，包括Windows与Linux两种系统下。(Java MyEclipse as the basic structures of the Java development environment IDE process, including Windows and Linux both systems.)

本资料的功能为：运用数学统计方法和时间序列分析方法对原始振动信号进行分析，获取相应的时域，频域，频域及时间序列模型参数并以此作为特征参数，然后运用距离区分技术进行评估，选取敏感的特征参数作为ART-similarity分类器的输入并进行训练，最后便可识别出设备的性能状态。 基于YU范数对承不同预紧状态的分析，针对进给系统所采集的数据样本事先不知其对应的状态时，则可利用基于YU范数的ART-Similarity监督分类器对其进行诊断分析。针对基于Yu范数ART-Similarity的算法，我上传的文件即为该算法的MATLAB代码，在matlab中，把文件中的关于"ryu0jin32feat.txt" "ryu1jin32feat.txt" "ryu2jin32feat.txt" "ryu3jin32feat.txt" "ryu4jin32feat.txt" "ryu5jin32feat.txt"文件的路径修改正确，即可正常运行，这些文件的主函数为"jingeiART.m"(This information is the function as follows: the use of mathematical statistical methods and time series analysis of the original vibration signal analysis, to obtain the corresponding time-domain, frequency domain, frequency domain and time-series model parameters and as a characteristic parameter, and then distinguish between the use of distance technology assess, select the characteristics of sensitive parameters as the ART-similarity classifier input and for training, the final performance of the device can identify the state. YU-based norm of the bearing preload status in different analysis systems for feeding the data collected samples know beforehand that the corresponding state, can make use of norm-based YU supervision of ART-Similarity Classifier diagnosis of them. Yu-based norm for the ART-Similarity of the algorithm, I uploaded the file shall be the algorithm MATLAB code, matlab, they have replaced the file on the "ryu0jin32feat.txt" "ryu1jin32feat.txt" "ryu2jin32feat.t)