资源列表
AndroidCalendar
- 自定义安卓日历，与原生日历不一样(Custom Android calendar app)
Seesaw Pendulum - VIs
- its for inverted pendlum
DropOut深度网络
- 深度神经网络在测试时面对如此大的网络是很难克服过拟合问题的。 Dropout能够很好地解决这个问题。通过阻止特征检测器的共同作用来提高神经网络的性能。这种方法的关键步骤在于训练时随机丢失网络的节点单元包括与之连接的网络权值。在训练的时候，Dropout方法可以使得网络变得更为简单紧凑。在测试阶段，通过Dropout训练得到的网络能够更准确地预测网络的输出。这种方式有效的减少了网络的过拟合问题，并且比其他正则化的方法有了更明显的提升。 本文通过一个简单的实验来比较使用Dropout方法前后网络
网关
- 自己编程获取网关地址： 需要修改系统注册表：给一段代码。供参考： //修改IP开始 if regRootKey.OpenKey('\SYSTEM\CurrentControlSet\Services\Tcpip\Parameters\Interfaces\' + CardList.Strings[cbb1.ItemIndex], True)(Self programming, obtaining gateway address, programming and obtaining
assignment2.1_gautam.tar
- assignment test2 of verilog which contains all questions answer.
Denish_Thummar_Verilog_Assignment_1.0.tar
- assignment 1.0 of verilog which contains all questions answer.
Denish_Thummar_Verilog_Assignment_1.1.tar
- assignment 1.1 of verilog which contains all questions answer.
Denish_Thummar_Verilog_Assignment_1.2.tar
- assignment 1.2 of verilog which contains all questions answer.
Denish_Thummar_Verilog_Assignment_1.3.tar
- assignment 1.3 of verilog which contains all questions answer.
IAR Multipication test
- MSP430 Launchpad integer mulitiplication
CTrayIconPosition_demo
- TrayIconPosition demonstration
CPPMessageBox_demo
- Message Box demonstation