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
*PC和ATMEGA128通信，ATMEGA以輪循方式發送，中斷方式接受*
上傳時間： 2014-10-09
上傳用戶：拔絲土豆
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.
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. 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 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 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，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 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-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
[解決方法] 對上述程序改動如下: 發送端: MMM SendBag ZeroMemory(&SendBag,sizeof(SendBag)) ............. int send = 0 while(send<sizeof(MMM)) { int nCharSend=send(m_hSocket,(char*)(&SendBag+send),sizeof(MMM)-send,0) send+=nCharSend } 接收端: MMM RecvBag ZeroMemory(&RecvBag,sizeof(RecvBag)) recv寫法同上while... 此方法適合傳送結構體的實現. 趕快試試看.
標簽： SendBag ZeroMemory sizeof MMM
上傳時間： 2013-12-03
上傳用戶：三人用菜
