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  • 孫鑫老師VC視頻第十九課代碼:動態(tài)鏈接庫程序的編寫。靜態(tài)庫與動態(tài)庫的區(qū)別

    孫鑫老師VC視頻第十九課代碼:動態(tài)鏈接庫程序的編寫。靜態(tài)庫與動態(tài)庫的區(qū)別,以及調(diào)用程序在鏈接靜態(tài)庫和動態(tài)庫時的區(qū)別。如何利用工具查看動態(tài)鏈接庫輸出的函數(shù),depends工具的使用,C++編譯器名字改編技術(shù)對動態(tài)鏈接庫輸出函數(shù)的影響,extern "C"的用法,利用模塊定義文件來解決C++名字改編的問題。用typedef定義指向函數(shù)的指針類型,如何獲得動態(tài)連接庫里的函數(shù)的指針。

    標簽: 視頻 代碼 動態(tài)鏈接庫 動態(tài)

    上傳時間: 2014-01-20

    上傳用戶:jing911003

  • 動態(tài)鏈接庫程序的編寫。靜態(tài)庫與動態(tài)庫的區(qū)別

    動態(tài)鏈接庫程序的編寫。靜態(tài)庫與動態(tài)庫的區(qū)別,以及調(diào)用程序在鏈接靜態(tài)庫和動態(tài)庫時的區(qū)別。如何利用工具查看動態(tài)鏈接庫輸出的函數(shù),depends工具的使用,C++編譯器名字改編技術(shù)對動態(tài)鏈接庫輸出函數(shù)的影響,extern "C"的用法,利用模塊定義文件來解決C++名字改編的問題。用typedef定義指向函數(shù)的指針類型,如何獲得動態(tài)連接庫里的函數(shù)的指針。

    標簽: 動態(tài)鏈接庫 動態(tài) 程序 編寫

    上傳時間: 2013-12-20

    上傳用戶:jkhjkh1982

  • one of video tool Skype only in windows mobile5.0 more than running, but my task is to let it run S

    one of video tool Skype only in windows mobile5.0 more than running, but my task is to let it run Skype in WINCE only in windows mobile5.0 more than running, but my task is to let it run in WINCE . Leave no stone unturned when I can not get windows mobile, they thought would be needed for skype all library files to my WINCE, so perhaps will be able to run skype. 1. Used depend Show skype depends on which files. In fact, not many documents, I can remember only under the following: core.dllcommctr.dllaygeshell.dllhtmlview.dll In addition to htmlview.dll, the other documents in WINCE have (if your system does not, please IMAGE Canada on the corresponding module). Therefore, I find on the Internet htmlview.dll, the results really find

    標簽: running windows mobile Skype

    上傳時間: 2014-01-17

    上傳用戶:miaochun888

  • Future+Mobile+Communications+LTE

    Providing QoS while optimizing the LTE network in a cost efficient manner is very challenging. Thus, radio scheduling is one of the most important functions in mobile broadband networks. The design of a mobile network radio scheduler holds several objectives that need to be satisfied, for example: the scheduler needs to maximize the radio performance by efficiently distributing the limited radio re- sources, since the operator’s revenue depends on it.

    標簽: Communications Future Mobile LTE

    上傳時間: 2020-05-27

    上傳用戶:shancjb

  • Smart+Grid

    The term “ smart grid ” defi nes a self - healing network equipped with dynamic optimiza- tion techniques that use real - time measurements to minimize network losses, maintain voltage levels, increase reliability, and improve asset management. The operational data collected by the smart grid and its sub - systems will allow system operators to rapidly identify the best strategy to secure against attacks, vulnerability, and so on, caused by various contingencies. However, the smart grid fi rst depends upon identifying and researching key performance measures, designing and testing appropriate tools, and developing the proper education curriculum to equip current and future personnel with the knowledge and skills for deployment of this highly advanced system.

    標簽: Smart Grid

    上傳時間: 2020-06-07

    上傳用戶:shancjb

  • Goldbort_Writing for Science

    Although doing science is at the heart of discovery, the effort would have very limited consequence in the long term without writingscience. As a social enterprise that depends on collaboration, scientific inquiry requires its practi- tioners to write on a regular basis. From time to time, some members of the scientific community have been critical of the overall quality of writing by re- searchers. 

    標簽: Goldbort_Writing Science for

    上傳時間: 2020-06-09

    上傳用戶:shancjb

  • Guide to Convolutional Neural Networks

    General paradigm in solving a computer vision problem is to represent a raw image using a more informative vector called feature vector and train a classifier on top of feature vectors collected from training set. From classification perspective, there are several off-the-shelf methods such as gradient boosting, random forest and support vector machines that are able to accurately model nonlinear decision boundaries. Hence, solving a computer vision problem mainly depends on the feature extraction algorithm

    標簽: Convolutional Networks Neural Guide to

    上傳時間: 2020-06-10

    上傳用戶:shancjb

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