搜索:CLOSE
找到约 96 项符合「CLOSE」的查询结果
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https://www.eeworm.com/dl/648/358288.html
单片机开发
uart全功能实现.实现如下函数: U_Open, U_Close, U_GetBytes, U_PutBytes, U_GetBytesAvail, U_GetTxRoomL
uart全功能实现.实现如下函数:
U_Open,
U_Close,
U_GetBytes,
U_PutBytes,
U_GetBytesAvail,
U_GetTxRoomLeft,
U_PutISRBytes,
U_GetTxISRRoomLeft,
U_Purge,
U_SetOwner,
U_SetFlowCtrl,
U_ConfigEscape,
U_SetDCBConfig,
U_CtrlDCD,
U_CtrlBreak,
U_ClrRxBuffer,
U_ClrTxBuffer,
...
https://www.eeworm.com/dl/532/386850.html
书籍源码
计算全息close all clc clear A=zeros(64) A(15:20,20:40)=1 A(15:50,20:25)=1 A(45:50,20:40)=1 A(30:34,
计算全息close all clc clear
A=zeros(64)
A(15:20,20:40)=1 A(15:50,20:25)=1
A(45:50,20:40)=1 A(30:34,20:35)=1
% ppp=exp(rand(64)*pi*2*i) A=A.*ppp
% Author s email: zjliu2001@163.com
figure imshow(abs(A),[])
Fa=fft2(fftshift(A)) Fs=fftshift(Fa)
Am=abs(Fs) % amplitude
Ph=ang ...
https://www.eeworm.com/dl/542/165924.html
其他书籍
无密码,按CLOSE就可. 本书图文并茂,循序渐进地介绍MATLAB5.X的主要功能、函数命令及一些使用技巧
无密码,按CLOSE就可.
本书图文并茂,循序渐进地介绍MATLAB5.X的主要功能、函数命令及一些使用技巧,并介绍了比较复杂的数值计算和图形用户界面的编写方法。本书重点介绍了神经网络的基本原理和学习训练算法。
https://www.eeworm.com/dl/625/183654.html
游戏
在一个450*350的窗体上在下面放置两个按钮“Start”和“Close”,连续点击“Start”按钮会在窗体上显示多个彩色的小球
在一个450*350的窗体上在下面放置两个按钮“Start”和“Close”,连续点击“Start”按钮会在窗体上显示多个彩色的小球,分别有红、绿、蓝三种颜色,小球不停的跳跃,碰到窗体的边缘则反弹。单击“Close”按钮则关闭整个程序 ...
https://www.eeworm.com/dl/633/412835.html
Java编程
Genetic Algorithm example using Java You have 10 cards numbered 1 to 10. You have to divide them i
Genetic Algorithm example using Java
You have 10 cards numbered 1 to 10.
You have to divide them into 2 piles so that:
The sum of the first pile is as close as possible to 36 and the product of all in second pile is as close as poss to 360.
https://www.eeworm.com/dl/920367.html
技术资料
INA105的简单修正电路用以增加放大器输出摆动
In many applications it is desirable for the output of anamplifier to swing close to its power s
https://www.eeworm.com/dl/681/129684.html
Oracle数据库
一个数据库连接池
一个数据库连接池,能捕获close方法,初始的时候指定初始化多少个连接,如果超过连接个数,则会自动递增连接个数,同时,在代码中可以直接调用close方法,程序会自动捕获
https://www.eeworm.com/dl/522498.html
论文
Densely Connected Convolutional Networks
Recent work has shown that convolutional networks can
be substantially deeper, more accurate, and efficient to train
if they contain shorter connections between layers close to
the input and those close to the output. In this paper, we
embrace this observation and introduce the D ...