Dali

说明：  Dentist Chair control cpu

LabVIEW实现对光谱的动态测量，并显示测量结果，动态测量的实现-LabVIEW realize spectra of dynamic measurement, and display measurement results, the realization of dynamic measurement

基于matlab的simulink的反激变换器仿真(Simulation of Simulink flyback converter based on MATLAB)

通过LS和DFT方法对OFDM实现了信道估计，并对估计后的信道同原始信道进行对比，还有不同信噪比下的误码仿真(Through LS and DFT method to achieve the OFDM channel estimation, and the estimated channel compared with the original channel, as well as the BER simulation under different signal to noise ratio )

Petri网中XML根结点为net,其属性有id、type，其子结点有四个，分别为token，place，transition，arc。根据传入矩阵生成Petri网(In Petri nets, the root node of XML is net, and its attributes are ID and type. There are four sub-nodes: token, place, transition and arc. Generating Petri Nets from Input Matrix)

Android输入法手势识别例子代码，android.gesture这个类在api-4(SDK1.6)才开始支持的！默认存到SD卡中，所以别忘记在AndroidMainfest.xml加上SD卡读写权限！测试时请您在紧凑的时间内用两笔划来完成一个手势！ 　　Himi提示：手势超过9个我做了删除所有手势的操作，为了界面整洁一些！输入法手势练习~(*^__^*)~ 嘻嘻！操作介绍：(画手势我设置必须画两笔划才行哦~)。 　　添加手势：先EditText中输入名称，然后在屏幕上画出手势！ 　　匹配手势：在EditText输入"himi",然后输入手势即可！ 　　这里抱怨一下，因为这里总是异常,今天仔细看了才发现不是没写权限,而是我虽然在AndroidMainfest.xml中写了权限，但是写错了位置..哭死！

北大青鸟，JS+JQuery内部测试机试题(beidaqingniaojsneibuceshiti)

指定预测变量的惩罚样条基础。这是通过拟合一组相对较小的样条并惩罚积分二阶导数来完成的。传统的平滑样条曲线每次观察使用一个基础，但是一些作者指出，对于大于自由度的2-3倍的任何数量的基函数，拟合的最终结果是难以区分的。Eilers和Marx指出，如果基函数是均匀间隔的，这会导致显着的计算简化，它们将结果称为p样条。(Specifies a penalised spline basis for the predictor. This is done by fitting a comparatively small set of splines and penalising the integrated second derivative. Traditional smoothing splines use one basis per observation, but several authors have pointed out that the final results of the fit are indistinguishable for any number of basis functions greater than about 2-3 times the degrees of freedom. Eilers and Marx point out that if the basis functions are evenly spaced, this leads to significant computational simplification, they refer to the result as a p-spline.)

说明：  Simulation simulink Prepared by: Shivananda Pukhrem

说明：  little C# client server application