Keil.STM32F4xx_DFP.2.11.0(分两包,第二包)
Keil.STM32F4xx_DFP.2.11.0(分两包,第二包) 官网下载的Keil.STM32H4xx_DFP.x.x.x.pack。亲测,OK。只需要下载,解压,安装.pack包到自己的KEIL安装路径即可(一般默认安装路径)
Keil.STM32F4xx_DFP.2.11.0(第一包)
Keil.STM32F4xx_DFP.2.11.0(分两包,第一包)
官网下载的Keil.STM32H4xx_DFP.x.x.x.pack。亲测,OK。只需要下载,解压,安装.pack包到自己的KEIL安装路径即可(一般默认安装路径)
Linux下的FAT分区修复软件源码_dosfstools-4.1
1.下载:dosfstools-3.0.0.tar.gz源码包
#tar zxvf dosfstools-3.0.0.tar.gz
#cd dosfstools-3.0.0
#make CC=arm-linux-gcc
2. 在当前目录下会生成mkdosfs,将该可执行文件(是可执行文件)拷贝到我们的开发板的文件系统/usr/sbin/ 目录下即可
#cp mkdosfs /home/nfs_root/first_fs/usr/sbin
EStreamEyeTools2.9.2.70710.7z
终于搞到了elecard的破解方法,复制以下两个文件到C:\Program Files\Common Files\Elecard文件夹下,覆盖原来的LC.dll,然后运行Registrator.exe,选中Elecard StreamEye Tools点击Activate,提示Enter Serial number,什么都不用填,直接OK即可.
Elecard.Streameye.Tools,一个强大的视频序列或码流分析软件,YUV分析,264文件分析软件,H.264视频编解码学习必备的东西,Elecard StreamEye Suite是一套用于专业视频压缩领域的功能强大的工具 ,能够帮助用户进行有效的对于视频序列的深入分析。感觉STREAM EYE的界面更加亲民,而且他的视频窗口可缩放,比较好操作,但是功能上面还是不如VISA强大,不过初学的话也是可以接受了。编码视频的可视化表现,流结构分析,这些流可以是MPEG-1/2/4 or AVC/H.264 VES(视频基本流)、SS(MPEG1的系统流)、,PS(MPEG2的程序流)、TS(mpeg2的传输流)。
UTF8转GBK,GBK转UTF8(GB2312)
本资源提供了一个完整的UTF8转GBK和GBK转UTF8的完整字库代码,需要用的朋友,欢迎下载,字库仅支持GB2312字库。超出GB2312字库的字符暂不支持。
NewNoteBook D6-XE7 Delphi VCL
一个不会让你看起来那么乱的NoteBook控件,非常好用,全系列Delphi均支持。只需要用到里面的一个pas文件即可。
TRichView 15.1 FS
TRichView 是Delphi/C++Builder 控件,主要用于显示、编辑和打印超文本文档。新版本解决多个兼容性问题,更新了字符串标签、剪贴板、RTF和DB组件。
兼容性问题
Item tags是字符串,不再是整数型
OnRVFPictureNeeded参数改变
TRichView.LoadText, LoadTextFromStream, SaveText, SaveTextToStream, TRichViewEdit.InsertTextFromFile 有了新的参数。
TRVLongOperation的声明类型已经改变
以下全局变量从RVTable.pas中移除:RichViewTableGridStyle, RichViewTableGridStyle2, RichViewTableGridColor,被替换为TRVStyle属性。
风格模板
默认情况下,风格模板不能被使用,需激活风格模板,设置TRichView.UseStyleTemplates = True。
在TRichViewEdit中,你可以应用指定的模板样式到选定区域,使用这些方法:ApplyStyleTemplate, ApplyTextStyleTemplate, ApplyParaStyleTemplate. 样式模板可用ChangeStyleTemplates方法编辑。
RTF
TRichView.RTFOptions中的新选项:rvrtfSavePngAsPng。如果默认有这个选项,PNG图像也会被保存为PNG格式。
打印
表格行的新属性: KeepTogether;
新的表格方法: SetRowPageBreakBefore, SetRowKeepTogether;
table.PrintOptions新选项: rvtoContinue;
新属性:TCustomRVPrint.IgnorePageBreaks。
旋转
表格单元格可旋转 90°, 180°或 270。
一个新的方法返回项坐标: GetItemCoordsEx; 它考虑到了单元格的旋转。
字符串标签
新属性:cell tags;
从13.2版本开始,项目标签是字符串(Unicode for Delphi 2009或更高,ANSI老版本的Delphi),从整数到PChar无需类型转换!
64-bit
32-bit 和 64-bit编译器均支持RAD Studio XE2+。
注意: TRVOfficeConverter 可以编译为64-bit应用程序,但列表的转换器将为空 (因为转换器是32-bit DLLs,不能再64-bit应用中使用)。
HTML存储
TRichView.SaveHTMLEx可保存扩展的背景图像;
TRichView.SaveHTMLEx 能更好的保存列表标记 (无论是在常规或rvsoMarkersAsText 模式);
TRichView.OnSaveImage2事件新增"hidden"参数。
DB组件
如果rvfoLoadBack在 RVFOptions中, TDBRichView会在加载数据前清空 BackgroundBitmap;
如果rvfoLoadBack在RVFOptions 和 FieldFormat=rvdbRVF中, TDBRichViewEdit会在加载数据前清空 BackgroundBitmap。
剪贴板
TRichViewEdit 可以粘贴URL,新增方法:PasteURL;
新属性:AcceptPasteFormats允许限制格式列表;
新属性:DefaultPictureVAlign定义一个对齐以粘贴和放置图像。
一个最简单的WINCE播放MP3示例(DSHOW)
一个在WINCE下面使用DSHOW播放音乐的示例,也是查看网上的示例代码写的。不过至少可以播放出MP3来。没有界面的。
GSPlayer225的源码
一个在WINCE平台下用的MP3播放器源码。希望能帮到大家。
C 语言编缉神经网络工具
NEURAL NETWORK PC TOOLS
SOFTWARE USER'S GUIDE
$Revision: 1.2 $ $Date: 02 Jan 1990 15:40:54 $
INTRODUCTION
The software described in this User's Guide is that described in the
chapter on Neural Network PC Tool Implementations in the book entitled
Neural Network PC Tools: A Practical Guide, to be published by
Academic Press in 1990. This software may be copied and distributed
AS LONG AS IT IS NOT MODIFIED. In particular, any problems with the
source code should be brought to the attention of the authors.
If you use this software, consider it as shareware and please send
$10.00 to the authors at the following address: Roy Dobbins, 5833
Humblebee Road, Columbia, MD 21045. As additions are made to this
software diskette, such as including self-organizing (Kohonen)
networks, the price will increase. It is anticipated that the price
for the diskette sold in conjunction with the book will be about $20.
BACKGROUND
Much excitement exists due to the apparent ability of artificial
neural networks to imitate the brain's ability to make decisions and
draw conclusions when presented with complex, noisy and/or partial
information. This software is for the engineer or programmer who is
interested in solving practical problems with neural networks.
It is a myth that the only way to achieve results with neural networks
is with a million dollars, a supercomputer, and an interdisciplinary
team of Nobel laureates. There are some commercial vendors out there
who would like you to believe that, though.
Using simple hardware and software tools, it is possible to solve
practical problems that are otherwise impossible or impractical.
Neural network tools (NNT's) offer a solution to some problems that
can't be solved any other way known to the authors.
THE BACK-PROPAGATION NNT: BATCHNET
This release contains both source and executable code for a "standard"
three layer back-propagation neural network. The executable program
is called batchnet.exe; its source code is in the file batchnet.c.
The program for generating random weights used as input to the
training run is weights.exe; its source code is in weights.c. These
files were compiled using Turbo C v 2.0, but can also be compiled in
Microsoft C.
They were compiled using the 80x87 emulator mode, so that they will
run even if you don't have a co-processor. If you have a coprocessor
and want batchnet to run faster, which may be especially important in
training, you can recompile batchnet.c using the 80x87 option. Always
use the compact model.
To run the batchnet program, you must specify the run file that it
will use. Demo.run is the run file for the demo.bat demonstration.
Look at the demo.bat and demo.run files to see what we mean.
Demo.bat also illustrates one of the options for batchnet. You can
specify the interval of iterations between average sum-squared error
printouts with the -e option: -e10 prints it out each 10 iterations.
The default number of iterations between error printouts is 100.
The other option for batchnet is to specify what average sum-squared
error (per output node and per pattern) is required for the program to
terminate training. The default value is 0.02: a command of -d.01
will override this with an error value of .01.
In the run file, you specify a number of things. Look at demo.run in
detail to see what they are; there is explanation following the run
data for the two runs that tell what goes where.
First, you specify the number of runs. The demo has two. This is
fairly typical. You often have a training run followed by a test run,
as is the case in the demo. You can, however, set up the software to
do as many runs as you want: hence the name "batchnet".
You then specify the filenames for a number of files: the output file
that gives the values of the output nodes for each pattern on the last
iteration (or the only iteration, if you are in testing mode and there
is only one iteration), the error file that gives you the average sum
squared error value each specified number of iterations, the source
pattern file (values normalized between 0 and 1), the input weights
file (generated by weights.exe for a training run, and consisting of
the output weights file from training for a testing run), and the
output weights file which gives you weight values after the last
iteration.
Note that the pattern files have values for each input node followed
by values for each output node followed by an ID field that you can
use to identify each pattern in some way. The input and output node
values should be between 0 and 1.
Following filenames, you specify, for each run, the number of input
patterns, the number of epochs (iterations of entire pattern set), the
number of input nodes, number of hidden nodes, number of output nodes,
the value for the learning coefficient (eta), and the value for the
momentum factor (alpha). The number of epochs varies a lot during
training, but often is in the range of 100-1000; during testing, you
only do one iteration.
Sample files are given that you can run with demo.bat; the output
files you will get when you run the demo are already on the diskette
as mytest.out, mytrain.out, mytrain.wts, mytest.wts, mytrain.err, and
mytest.err. You will get similar files without the "my" prefix when
you run the demo.bat program, and you can compare corresponding files
to see that they are the same.
All you have to do is run "demo.bat" in order to both train and test
the batchnet artificial neural network on the patterns in the
train.pat and test.pat files. These pattern files are built from
actual electroencephalogram (EEG) spike parameter data, and illustrate
the use of a parameter-based NNT.
The training phase of the demo.bat will probably take about 45 minutes
on a 4.77 MHz 8088 PC with coprocessor. A 12 MHz Compaq with
coprocessor takes about 18 minutes. A 10 MHz Grid 80286 Laptop with
no coprocessor takes about 140 minutes. The coprocessor makes the
difference!
HINTON DIAGRAMS
Overview
This program displays Hinton diagrams - graphical representations of
neural network weights. The program assumes that the weights for a
three layer network have been stored in a disk file as ASCII floating
point numbers. An example of a valid weights file that you have on
this shareware diskette is mytrain.wts.
System Requirements
You need a PC with EGA or VGA to run this. We have never tried it on
a CGA, but in theory you should be able to get something there too.
Ensure that the necessary driver files are all present in the
directory from which HINTON.EXE is run:
HINTON.EXE
EGAVGA.BGI
CGA.BGI
Use
To use the program, at the DOS prompt type:
hinton {-c} datafile input hidden output
-c no color
datafile name of data file
input number of units in input layer
hidden number of units in hidden layer
output number of units in output layer
Use the -c option if you have a monochrome screen or if you want to
make hardcopies of the screen.
Currently HINTON.EXE only works with three layer feedforward networks.
Data File Organization
The file must be in the form of ASCII text floating point numbers, in
the order given below:
data_file is :-
input_layer_to_hidden_layer_weights
hidden_layer_to_output_layer_weights
input_layer_to_hidden_layer_weights is:-
weights_for_hidden_unit 0
weights_for_hidden_unit 1
weights_for_hidden_unit 2
...
weights_for_hidden_unit h-1
hidden_layer_to_output_layer_weights is :-
weights_for_output_unit_0
weights_for_output_unit_1
weights_for_output_unit_2
...
weights_for_output_unit_o-1
weights_for_hidden_unit_n is :-
weight from input unit 0 to hidden unit n
weight from input unit 1 to hidden unit n
weight from input unit 2 to hidden unit n
...
weight from input unit i-1 to hidden unit n
weight from bias unit to hidden unit n
weights_for_output_unit_n is :-
weight from hidden unit 0 to output unit n
weight from hidden unit 1 to output unit n
weight from hidden unit 2 to output unit n
...
weight from hidden unit h-1 to output unit n
weight from bias unit to output unit n
Note that although you must have the weights from the bias units
present in the file, the current version of hinton.exe does not
portray the bias weights. This will be changed in the next version of
hinton.exe.
Menu
The main menu consists of the following commands, displayed in a bar
at the bottom of the screen:
Hidden Out View Clear Zoom Shrink Flip Unit Range Quit
Brief description of commands:
Hidden
Activate the hidden layer window. Does not alter the display, but all
future commands are directed to this window (A later version of
HINTON.EXE will give a positive indication of the activated window).
Out
Activate the output layer window.
View
Display (or re-display) the data in the current window. Values are
displayed as small filled rectangles. The area of a rectangle is
proportional to the magnitude, while the color and fill pattern
indicate the sign. Currently, positive numbers are displayed in white
while negative numbers are displayed in color, the color varying from
layer to layer - blue for hidden, red for output.
Printscreen
Not a menu command. To get a hardcopy of the Hinton diagrams, you
must load your favorite hot key utility for your CGA, EGA or VGA
screen. Furthermore, to get a good representation on a black and
white printer, you should run hinton -c to suppress on-screen color
information, as indicated in the command line description.
Clear
Clear the current window (does not alter the data in any way; merely
erases the display window).
Zoom
Increase the magnification of the current window. The opposite of
Shrink. Data is scaled up and appears larger in the window. It is
possible that some of the image will be clipped, if it now falls
outside the window boundaries.
Shrink
Decrease the magnification of the current window. The opposite of
Zoom. Data is scaled down and appears smaller in the window. The
minimum shrinkage is down to the level of one pixel, after which
further Shrink commands are ignored.
Flip
Turn the image in the window through 90 degrees. Horizontally
organized data is displayed vertically and vice versa. This command
acts as a toggle. A subsequent Flip command rotates the image back
through 90 degrees back to its original orientation.
Unit
Specify the unit(s) of the current layer, that are to be displayed in
the window. The default is all units. You can enter a single unit or
you can enter a range as a pair of numbers. For example, to display
units 10 through 15, enter: 10 15
Range
Specify the units of the input to the current layer that are to be
dislayed in the window. The default is all input units. You can
enter a single unit or you can enter a range as a pair of numbers.
Quit
Quit the program. The mode of the screen is changed from graphics
back to the normal text mode of the PC.
Simple Example of Running the Hinton Program
To look at the weight values in the file "mytrain.wts", which has
weights for a 9-4-2 node backprop network, just run the hinton.exe
program with the following command: hinton mytrain.wts 9 4 2
You then see a blank screen with the prompts below. You are by
default in the hidden layer window that shows the weights from the
input to the hidden layer. To see the hidden weights, hit the V key,
for view. Hit Z for zoom to enlarge the weights.
To see the weights in the output layer, hit O for output layer. This
puts you in the output window. Then hit V for view; Z for zoom, etc.
3D图形编程指南 西北工业大学电子工程系 刘长松 程连冀(译)
总目录
第一章 硬件接口
1.1 3D应用程序与硬件的交互作用
1.1.1 在计算机屏幕上显示图像
1.1.2 事件反应
1.2 使用不同的体系结构
1.2.1 MS-DOS.
1.2.2 MS-Windows.
1.2.3 X11.
1.2.4 NeXTStep.
1.2.5 MacOS.
第二章 3D变换
2.1 欧几里得空间,自由度和基本变换
2.2 平移
2.3 缩放
2.4 在平面内旋转
2.5 3D旋转
2.5.1 坐标系
2.5.2 变换次序
2.6 以矩阵形式表达变换
2.7 投影变换
2.7.1 平行投影
2.7.2 透视投影
2.8 通过定点算法实现变换
2.8.1 整型数表示
2.8.2 定点数运算
2.8.3 定点算法的实现
第三章 2D图元光栅处理
3.1 光栅化点
3.2 光栅化线段
3.3 光栅化多边形
3.3.1 光栅化凸多边形
3.3.2 光栅化凹多边形
3.4 内插渲染明暗处理的多边形
3.5 渲染纹理多边形
3.6 反走样
第四章 2D和3D裁剪
4.1 2D裁剪策略
4.1.1 点的裁剪
4.1.2 裁剪线段
4.1.3 裁剪多边形
4.2 3D裁剪策略
第五章 视处理
5.1 从世界到屏幕的方法
5.1.1 视系统参数
5.1.2 多边形管道
5.1.3 纹理多边形
5.2 从屏幕到世界的方法
5.2.1 直线方程
5.2.2 平面方程
5.2.3 直线和平面的交叉点
5.2.4 直线和多边形的交叉点
5.2.5 直线和球的交叉点
5.2.6 寻找合适的交叉点
5.2.7 优化光线追踪
第六章 建模
6.1 线框模型
6.2 多边形模型
6.3 三次曲线和双三次曲面
6.4 地形
6.5 体素模型
第七章 隐面消除
7.1 背面剔除算法
7.2 从后到前排序
7.3 顺序列表和八叉树
7.4 入口
7.5 二叉空间分割树
7.6 Beam树
7.7 扫描线算法
7.8 Z-buffer算法
第八章 光线
8.1 光线的物理特性与人的感觉
8.2 颜色模拟
8.2.1 非彩色光
8.2.2 颜色模型的三个成分
8.3 照明模拟
8.3.1 环境照明
8.3.2 漫反射
8.3.3 镜面反射
8.4 在屏幕到世界中观察照明
8.5 辐射度
8.6 在世界到屏幕中观察照明
第九章 构建3-D应用程序的实践方面
9.1 常规设计方法
9.1.1 面向对象编程
9.1.2 脚本
9.2 构建工具
9.2.1 OpenGL
9.2.2 Direct3D
9.3 应用程序的构建策略
9.3.1 实体视处理
9.3.2 室内场景视处理
9.3.3 室外场景视处理
附录
10.1 参考文献
10.2 常用公式
Delphi6联机中文帮助
关于版权
本参考中所有以Original标明的内容,均原文出自Delphi 6帮助系统,版权归Borland/Inprise公司所有。
本参考中所有以译文和/或编者注标明的内容,均系编者个人观点,而不作为Borland/Inprise公司发布的内容,版权归编者所有。
本参考纯粹作为学习和研究之用,不提供任何商业用途,故请使用者切勿侵犯Borland/Inprise公司版权及编者版权。
谅解声明
如果您发现本参考侵犯了任何企业、团体、公司、个人等的版权,请您立即停止使用并及时通知编者以停止版权侵犯。
本参考纯粹编者一家之言,疏漏和错误之处难免存在,欢迎批评指正,编者将做及时更新。
注意
本参考对任何团体和个人都完全免费且无任何附加条件。
欢迎通过E-mail向本人索取最新版本(建议邮件主题为:Fetch Object Pascal Reference)。
联系编者
Email1:
[email protected]
Email2:
[email protected]
OICQ: 123010445
网络数据监视工具 FSTools组合工具
这是一个用于网络编程中的调试工具,它可以抓去ICMP,TCP,UDP数据包,在进行网络通信编程时可以验证数据是否已经发送、是否已经发送成功;同时它也是一个不错的网络协议分析工具。