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Implements

  • a3load is 8051 firmware that can be used for uploading or downloading to EZ-USB RAM (internal or ex

    a3load is 8051 firmware that can be used for uploading or downloading to EZ-USB RAM (internal or external). It Implements the vendor specific command bRequest = 0xA3. The address to download/upload to/from is specified in the wValue field of the SETUP packet and the length of the transfer in the wLength field. The actual upload/download data is transferred during the DATA stage of the SETUP transfer. This firmware will function on all EZ-USB chips (EZ-USB, EZ-USB FX, FX2, FX2LP, FX1).

    标签: downloading uploading firmware internal

    上传时间: 2013-12-25

    上传用户:zhaiye

  • SWI with ARTX Kernel and RealView Compiler This example program shows how to implement software int

    SWI with ARTX Kernel and RealView Compiler This example program shows how to implement software interrupt functions in an application that uses the ARTX Kernel. The example uses the RealView Compilation Tools. The file SWI_Table.s Implements the SWI function table. The SWI function declarations and implementations are demonstrated in the file Artx_SWI.c.

    标签: implement Compiler RealView software

    上传时间: 2015-05-30

    上传用户:chenlong

  •  ? Java函数速查 你能很快的查到你要的函数 DataBinding类 代表数据源字段和组件属性之间一个单独的绑定。 package com.ms.wfc.data.ui

     ? Java函数速查 你能很快的查到你要的函数 DataBinding类 代表数据源字段和组件属性之间一个单独的绑定。 package com.ms.wfc.data.ui public class DataBinding Implements IConstructable 说明 DataBinder控件使用该类来表示数据源中的每一个绑定。 请参阅:《Microsoft Visual J++ 6.0 程序员指南》第18章“WFC中的数据绑定”。 构造器 DataBinding.DataBinding 创建一个DataBinding对象。 语法 public DataBinding () public DataBinding ( IComponent target, String propertyName,String fieldName ) public DataBinding ( IComponent target, String propertyName,String fieldName, IDataFormat format )

    标签: DataBinding package Java data

    上传时间: 2013-12-20

    上传用户:TRIFCT

  • This collection of C++ templates wraps the FORTRAN or C interfaces for LAPACK so that they integrate

    This collection of C++ templates wraps the FORTRAN or C interfaces for LAPACK so that they integrate with the Boost uBLAS library. Currently Implements Cholesky decomposition, LU decomposition, inversion and determinant for general and positive-definite matrices.

    标签: collection interfaces integrate templates

    上传时间: 2015-08-10

    上传用户:chfanjiang

  • Dropbear is an SSH 2 server, designed to be usable in small memory environments. It supports:

    Dropbear is an SSH 2 server, designed to be usable in small memory environments. It supports: * Main features of SSH 2 protocol * Implements X11 forwarding, and authentication-agent forwarding for OpenSSH clients * Compatible with OpenSSH ~/.ssh/authorized_keys public key authentication

    标签: environments Dropbear designed supports

    上传时间: 2014-01-16

    上传用户:skhlm

  • java 数据库 功能强大 效率高 SmallSQL Database is a free DBMS library for the Java(tm) platform. It runs on

    java 数据库 功能强大 效率高 SmallSQL Database is a free DBMS library for the Java(tm) platform. It runs on the Java 2 Platform (JDK 1.4 or later) and Implements the JDBC 3.0 API. SmallSQL Database is licensed under the terms of the GNU Lesser General Public Licence (LGPL). A copy of the licence is included in the distribution. Please note that SmallSQL Database is distributed WITHOUT ANY WARRANTY without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. Please refer to the licence for details.

    标签: SmallSQL Database platform library

    上传时间: 2013-12-19

    上传用户:yyyyyyyyyy

  • rdesktop is a client for Microsoft Windows NT Terminal Server, Windows 2000 Terminal Services, Wind

    rdesktop is a client for Microsoft Windows NT Terminal Server, Windows 2000 Terminal Services, Windows 2003 Terminal Services/Remote Desktop, Windows XP Remote Desktop, and possibly other Terminal Services products. rdesktop currently Implements the RDP version 4 and 5 protocols.

    标签: Terminal Windows Microsoft rdesktop

    上传时间: 2013-12-19

    上传用户:liuchee

  • This directory builds the Tape class driver for Microsoft® Windows® Server 2003. The class dri

    This directory builds the Tape class driver for Microsoft® Windows® Server 2003. The class driver Implements device-independent support, and exports support routines for device-specific tape miniclass drivers. It handles device-independent tape requests and calls the tape minidriver routines to process device-specific functions. Class driver splits transfer requests, when necessary, to fit the maximum transfer size for the underlying host bus adapter. It also provides device-independent, tape-specific error handling, and calls the tape miniclass driver s device-specific error handling routines.

    标签: class Microsoft directory reg

    上传时间: 2013-12-09

    上传用户:huangld

  • java语言开发的P2P流媒体系统

    java语言开发的P2P流媒体系统,“Stream-2-Stream Implements multicast+, a next generation streaming protocol. Multicast+ is more efficient and requires less bandwidth than direct streaming (e.g. shoutcast/icecast). Stream-2-Stream (abbreviated "s2s" or "S2S") stations have no user limit stations can be set up without paying a fortune for bandwidth. Stream-2-Stream saves bandwidth by passing streams from one peer to another through multicast and unicast p2p, rather than everyone getting a stream from one central server (Shoutcast/Icecast). ”更多:http://s2s.sourceforge.net/about.php

    标签: java P2P 语言 流媒体系统

    上传时间: 2016-01-09

    上传用户:ikemada

  • Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form

    Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) Implements this idea as a greedy search for a linear combination of classifiers by overweighting the examples that are misclassified by each classifier. icsiboost Implements Adaboost over stumps (one-level decision trees) on discrete and continuous attributes (words and real values). See http://en.wikipedia.org/wiki/AdaBoost and the papers by Y. Freund and R. Schapire for more details [1]. This approach is one of most efficient and simple to combine continuous and nominal values. Our implementation is aimed at allowing training from millions of examples by hundreds of features in a reasonable time/memory.

    标签: meta-learning classifiers combining Boosting

    上传时间: 2016-01-30

    上传用户:songnanhua