倒立摆系统设计

用户管理权限项目，使用java实现的版本，内有数据库脚本(User management privilege project, using the version implemented in java, with database scripts)

说明：  参照文献搭建了永磁同步电机直接转矩控制模型； 适合做毕业设计时参考，也非常适合新手学习； 可在该模型的基础上，根据自己的研究需要添加卡尔曼滤波、预测控制、占空比直接转矩等。(The direct torque control model of permanent magnet synchronous motor (PMSM) is built according to the literature; Suitable for graduation design reference, also very suitable for novice learning; On the basis of this model, Kalman filter, predictive control, duty cycle and direct torque can be added according to our own research needs)

这是3篇关于ST simpleMac 通信协议开发的问题，有兴趣的可以看一下(there are 3 paper about st simplemac development )

一个小的瞬变电磁测深数据处理程序，主要用于计算视电阻率和深度-a small transient electromagnetic sounding data processing procedures, mainly used in the calculation of the apparent resistivity and depth

常用的盲分离算法有二阶统计量方法、高阶累积量方法、信息最大化（ Infomax ）以及独 立成分分析（ ICA ）等。这些方法取得最佳性能的条件总是与源信号的概率密度函数假设有关， 一旦假设的概率密度与实际信号的密度函数相差甚远，分离性能将大大降低。本文提出采用 核函数密度估计的方法进行任意信号源的盲分离，并通过典型算例与几种盲分离算法进行了 性能比较，验证了方法的可行性。(The commonly used blind separation algorithms include two order statistics, higher order cumulants, and maximization of information Infomax) and independent component analysis (ICA). The conditions for obtaining the best performance of these methods are always related to the hypothesis of the probability density function of the source signal. The separation performance will be greatly reduced when the assumed probability density is very different from the density function of the actual signal. In this paper, a method of kernel function density estimation for blind separation of arbitrary signal sources is proposed. The performance of several blind separation algorithms is compared with some typical examples, and the feasibility of the method is verified.)

BX-5MK2 Technical parameters

Advanced Digital Communications (EQ2411)

VB精仿 Regedit win7 注册表，在Windows XP下也同样运行稳定，精仿的注册表，不管是从界面还是功能上来说，几乎和Windows7自带的注册表编辑器一模一样的。从键值和结构等各个方面，甚至还要优于windows注册表，键值设置界面功能比较多，注册表运行效果如图所示，是不是很强大？

python datamining python 数据挖掘实战(python datamining Data mining practice useful code in study)

classic game is developed in javaME platform.