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while

while是計算機的一種基本循環模式。當滿足條件時進入循環,進入循環后,當條件不滿足時,跳出循環。while語句的一般表達式為:while(表達式){循環體}。
  • 89s51單片機控制繼電器! 由s51io口輸出低電平使三極管導通 從而控制繼電器閉合 #include <reg51.H> sbit P0_0=P0^0 sbit P1_

    89s51單片機控制繼電器! 由s51io口輸出低電平使三極管導通 從而控制繼電器閉合 #include <reg51.H> sbit P0_0=P0^0 sbit P1_7=P1^7 main() {while(1) { if (P0_0==0) P1_7==1 } }

    標簽: sbit include 89s51 51

    上傳時間: 2013-12-17

    上傳用戶:xsnjzljj

  • jsp和xml。XML and JSP are two important tools available in producing a web application. This chapter e

    jsp和xml。XML and JSP are two important tools available in producing a web application. This chapter examines the potential of mixing these two technologies in order to enhance the capabilities of JSP. while this chapter will cover many things about XML, this chapter will not attempt to teach XML. Instead it focuses on how JSP and XML can be used together as a highly flexible and powerful tool. In general the usage of XML in these examples will be kept simple and should cause no problems for users who are starting XML.

    標簽: application important available producing

    上傳時間: 2013-12-10

    上傳用戶:1427796291

  • To find and output 11-999 between the number of m, it is to meet m, m2 and m3 are several palindrome

    To find and output 11-999 between the number of m, it is to meet m, m2 and m3 are several palindrome. The so-called palindrome refers to the number of its symmetrical figures that the whole number, for example, 121,676,94249 and so on. To meet the above requirements, such as the number of m = 11, m2 = 121, m3 = 1331 palindrome are few. Please prepare function int svalue (long m) to achieve this function, if it is palindrome, is a function to return, while return 0.

    標簽: palindrome and between several

    上傳時間: 2013-12-27

    上傳用戶:二驅蚊器

  • Inside the C++ Object Model Inside the C++ Object Model focuses on the underlying mechanisms that s

    Inside the C++ Object Model Inside the C++ Object Model focuses on the underlying mechanisms that support object-oriented programming within C++: constructor semantics, temporary generation, support for encapsulation, inheritance, and "the virtuals"-virtual functions and virtual inheritance. This book shows how your understanding the underlying implementation models can help you code more efficiently and with greater confidence. Lippman dispells the misinformation and myths about the overhead and complexity associated with C++, while pointing out areas in which costs and trade offs, sometimes hidden, do exist. He then explains how the various implementation models arose, points out areas in which they are likely to evolve, and why they are what they are. He covers the semantic implications of the C++ object model and how that model affects your programs.

    標簽: Inside Object the Model

    上傳時間: 2013-12-24

    上傳用戶:zhouli

  • This document contains official rules of the 3D soccer simulation competition at RoboCup 2006. Whil

    This document contains official rules of the 3D soccer simulation competition at RoboCup 2006. while we will try to cover all cases, if unexpected events do occur, the rule committee will seek input from the participants and then make a decision. However, once the committee has made a decision, that decision is final and will not be open to further discussion

    標簽: competition simulation document contains

    上傳時間: 2016-11-30

    上傳用戶:zhengzg

  • I often need a simple function generator. Just to generate a certain frequency. After all the years

    I often need a simple function generator. Just to generate a certain frequency. After all the years I ve worked with electronics, I still haven t got me one. Even though I need it now and then, I just couldn t seem to justify the cost of one. So, standard solution - build one yourself. I designed a simple sinewave generator based on a Analog Devices AD9832 chip. It will generate a sinewave from 0.005 to 12 MHz in 0.005 Hz steps. That s pretty good, and definitely good enough for me ! But while waiting for the AD9832 chip to arrive, I came up with a very simple version of the DDS synth, using just the 2313 and a resistor network.

    標簽: frequency generator function generate

    上傳時間: 2013-12-17

    上傳用戶:thesk123

  • The TMS320LF240xA and TMS320LC240xA devices, new members of the TMS320C24x generation of dig

    The TMS320LF240xA and TMS320LC240xA devices, new members of the TMS320C24x generation of digital signal processor (DSP) controllers, are part of the TMS320C2000 platform of fixed-point DSPs. The 240xA devices offer the enhanced TMS320 DSP architectural design of the C2xx core CPU for low-cost, low-power, and high-performance processing capabilities. Several advanced peripherals, optimized for digital motor and motion control applications, have been integrated to provide a true single-chip DSP controller. while code-compatible with the existing C24x DSP controller devices, the 240xA offers increased processing performance (40 MIPS) and a higher level of peripheral integration. See the TMS320x240xA Device Summary section for device-specific features.

    標簽: TMS 320 generation 240

    上傳時間: 2013-12-16

    上傳用戶:GavinNeko

  • MyTask、YouTask和ThreeTask 。在主函數中創建任務MyTask。而YouTask和ThreeTask由任務MyTaskTask創建

    MyTask、YouTask和ThreeTask 。在主函數中創建任務MyTask。而YouTask和ThreeTask由任務MyTaskTask創建,其優先級分別為2、4、6。這三個任務都要占用資源s,任務YouTask訪問時間短一些,在任務MyTask和任務ThreeTask利用while(OSTime<T) {}增加訪問時間,T值分別為300,500。MyTask、YouTask和ThreeTask采用OSTimeDly(K)延時等待,K值均為200。這樣出現任務優先級反轉。為了解決優先級反轉,設計何種信號量既解決此問題。請先指出任務優先級反轉出現在哪里? 后顯示克服過程

    標簽: ThreeTask YouTask MyTask MyTaskTask

    上傳時間: 2016-12-23

    上傳用戶:tb_6877751

  • Batch version of the back-propagation algorithm. % Given a set of corresponding input-output pairs

    Batch version of the back-propagation algorithm. % Given a set of corresponding input-output pairs and an initial network % [W1,W2,critvec,iter]=batbp(NetDef,W1,W2,PHI,Y,trparms) trains the % network with backpropagation. % % The activation functions must be either linear or tanh. The network % architecture is defined by the matrix NetDef consisting of two % rows. The first row specifies the hidden layer while the second % specifies the output layer. %

    標簽: back-propagation corresponding input-output algorithm

    上傳時間: 2016-12-27

    上傳用戶:exxxds

  • Train a two layer neural network with a recursive prediction error % algorithm ("recursive Gauss-Ne

    Train a two layer neural network with a recursive prediction error % algorithm ("recursive Gauss-Newton"). Also pruned (i.e., not fully % connected) networks can be trained. % % The activation functions can either be linear or tanh. The network % architecture is defined by the matrix NetDef , which has of two % rows. The first row specifies the hidden layer while the second % specifies the output layer.

    標簽: recursive prediction algorithm Gauss-Ne

    上傳時間: 2016-12-27

    上傳用戶:ljt101007

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