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Long-distance

  • It may analyze the window structure, the advancement and the window news, has the very greatly auxil

    It may analyze the window structure, the advancement and the window news, has the very greatly auxiliary function to the development work. When we need to study some object, so long as assigns out its search window, drives the detector the indicator to assign the window/to control on to release then. Under, the author on and everybody same place, makes with VC to belong to own Spy++.

    标签: the window advancement structure

    上传时间: 2013-12-31

    上传用户:ghostparker

  • Dijkstra算法求最短路径(C#版) using System using System.Collections using System.Text namespace Greedy

    Dijkstra算法求最短路径(C#版) using System using System.Collections using System.Text namespace Greedy { class Marx { private int[] distance private int row private ArrayList ways = new ArrayList() public Marx(int n,params int[] d) { this.row = n distance = new int[row * row] for (int i = 0 i < row * row i++) { this.distance[i] = d[i]

    标签: System using Collections namespace

    上传时间: 2013-12-29

    上传用户:liglechongchong

  • 2.0.12 (May 13th, 2004) - Flag driver threads with PF_FREEZE to support software suspend. 2.0.

    2.0.12 (May 13th, 2004) - Flag driver threads with PF_FREEZE to support software suspend. 2.0.11 (May 7th, 2004) - Avoid split-completion bugs in certain PCI-X chipsets by breaking up large completion entry DMAs on ADB boundaries. 2.0.10 (April 9th, 2004) - Return "command timeout" status instead of "selection timeout status" to the SCSI mid-layer in response to selection timeouts. While the latter may seem more correct, the mid-layer will not offline devices suffering from persistent selection timeouts. This leads to extremely long recovery times for devices that go missing. Returning command timeout status causes the mid-layer to enter recovery and eventually offline persistently missing devices.

    标签: PF_FREEZE software support suspend

    上传时间: 2016-01-05

    上传用户:亚亚娟娟123

  • The TMS320C64x™ DSPs (including the TMS320DM642 device) are the highest-performance fixed-point

    The TMS320C64x™ DSPs (including the TMS320DM642 device) are the highest-performance fixed-point DSP generation in the TMS320C6000™ DSP platform. The TMS320DM642 (DM642) device is based on the second-generation high-performance, advanced VelociTI™ very-long-instruction-word (VLIW) architecture (VelociTI.2™ ) developed by Texas Instruments (TI), making these DSPs an excellent choice for digital media applications. The C64x™ is a code-compatible member of the C6000™ DSP platform.

    标签: highest-performance fixed-point TMS 320

    上传时间: 2013-12-21

    上传用户:watch100

  • DELPHIBOX The ImageHTML converts images to ASCII characters in HTML format. The output image is in

    DELPHIBOX The ImageHTML converts images to ASCII characters in HTML format. The output image is in three formats: true color, grayscale, and mono color. The ImageHTML is provided "AS IS " without any warranty of any kind, either express or implied. The entire risk as to the quality and performance of the software is with you. The author is not liable for any damages resulting from the use and misuse of the software. The ImageHTML is freeware. You may copy it as long as you copy all of files.

    标签: characters DELPHIBOX The ImageHTML

    上传时间: 2013-12-27

    上传用户:zhichenglu

  • As all of you know, MATLAB is a powerful engineering language. Because of some limitation, some task

    As all of you know, MATLAB is a powerful engineering language. Because of some limitation, some tasks take very long time to proceed. Also MATLAB is an interpreter not a compiler. For this reason, executing a MATLAB program (m file) is time consuming. For solving this problem, Mathworks provides us C Math Library or in common language, MATLAB API. A developer can employ these APIs to solve engineering problems very fast and easy. This article is about how can use these APIs.

    标签: some engineering limitation language

    上传时间: 2013-12-06

    上传用户:huql11633

  • How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters S

    How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.

    标签: the decision clusters Cluster

    上传时间: 2013-12-21

    上传用户:gxmm

  • 查找字符串 TABLE DB "ABCDEFGHIKLMNOPQRSTUVWYZ" STR1 DB "Please enter a string:",0DH,0AH,"$" STR2 DB "Wr

    查找字符串 TABLE DB "ABCDEFGHIKLMNOPQRSTUVWYZ" STR1 DB "Please enter a string:",0DH,0AH,"$" STR2 DB "Wrong! The string is too long!"$"

    标签: ABCDEFGHIKLMNOPQRSTUVWYZ DB Please string

    上传时间: 2014-11-30

    上传用户:hfmm633

  • 压缩解压算法LZ77算法有许多派生算法(这里面包括 LZSS算法)。它们的算法原理上基本都相同

    压缩解压算法LZ77算法有许多派生算法(这里面包括 LZSS算法)。它们的算法原理上基本都相同,无论是哪种派生算法,LZ77算法总会包含一个动态窗口(Sliding Window)和一个预读缓冲器(Read Ahead Buffer)。动态窗口是个历史缓冲器,它被用来存放输入流的前n个字节的有关信息。一个动态窗口的数据范围可以从 0K 到 64K,而LZSS算法使用了一个4K的动态窗口。预读缓冲器是与动态窗口相对应的,它被用来存放输入流的前n个字节,预读缓冲器的大小通常在0 – 258 之间。这个算法就是基于这些建立的。用下n个字节填充预读缓存器(这里的n是预读缓存器的大小)。在动态窗口中寻找与预读缓冲器中的最匹配的数据,如果匹配的数据长度大于最小匹配长度 (通常取决于编码器,以及动态窗口的大小,比如一个4K的动态窗口,它的最小匹配长度就是2),那么就输出一对〈长度(length),距离(distance)〉数组。长度(length)是匹配的数据长度,而距离(distance)说明了在输入流中向后多少字节这个匹配数据可以被找到。

    标签: 算法 LZSS LZ 77

    上传时间: 2014-01-22

    上传用户:tzl1975

  • Computes BER v EbNo curve for convolutional encoding / soft decision Viterbi decoding scheme assum

    Computes BER v EbNo curve for convolutional encoding / soft decision Viterbi decoding scheme assuming BPSK. Brute force Monte Carlo approach is unsatisfactory (takes too long) to find the BER curve. The computation uses a quasi-analytic (QA) technique that relies on the estimation (approximate one) of the information-bits Weight Enumerating Function (WEF) using A simulation of the convolutional encoder. Once the WEF is estimated, the analytic formula for the BER is used.

    标签: convolutional Computes encoding decision

    上传时间: 2013-12-24

    上传用户:咔乐坞