SharpZipLib之前叫做NZipLib，完全由 C# 開發的壓縮庫，支持Zip, GZip, Tar and BZip2 ，為2007年8月最新0852release版的源文件和文檔說明！
Changes for v0.85.2 release
Minor tweaks for CF, ZipEntryFactory and ZipFile.
Fix for zip testing and Zip64 local header patching.
FastZip revamped to handle file attributes on extract + other fixes
Null ref in path filter fixed.
Extra data handling fixes
Revamped build and conditional compilation handling
Many bug fixes for Zip64.
Minor improvements to C# samples.
ZIP-1341 Non ascii zip password handling fix.
ZIP-355 Fix for zip compression problem at low levels
SharpZipLib之前叫做NZipLib，完全由 C# 開發的壓縮庫，支持Zip, GZip, Tar and BZip2 ，為2007年8月最新0852release版的代碼實例！
Changes for v0.85.2 release
Minor tweaks for CF, ZipEntryFactory and ZipFile.
Fix for zip testing and Zip64 local header patching.
FastZip revamped to handle file attributes on extract + other fixes
Null ref in path filter fixed.
Extra data handling fixes
Revamped build and conditional compilation handling
Many bug fixes for Zip64.
Minor improvements to C# samples.
ZIP-1341 Non ascii zip password handling fix.
ZIP-355 Fix for zip compression problem at low levels
This package consists of the executable (UCW), a default script file,
this file, and the library files. It is important that the header files
end up in a include subdirectory of the directory where UCW is found.
If you unzip this file using its path information ( use folder names ) this will
automatically happen. You can optionally specify the UnderC directory
with the environment variable UC_HOME note that this points to the directory
containing ucw.exe. If you do this, then you can copy the executable anywhere
and it will still be able to find the header files.
Welcome to UnderC version 1.2.9w
This package consists of the executable (UCW), a default script file,
this file, and the library files. It is important that the header files
end up in a include subdirectory of the directory where UCW is found.
If you unzip this file using its path information ( use folder names ) this will
automatically happen. You can optionally specify the UnderC directory
with the environment variable UC_HOME note that this points to the directory
containing ucw.exe. If you do this, then you can copy the executable anywhere
and it will still be able to find the header files.
Matrix TCL Lite 1.12
This matrix C++ template class library is for performing common matrix operations in your C++ program like any other built-in data types. To install the package, just copy MATRIX.H file into the INCLUDE directory of your compiler and include this header file in your program source file.
This article describes a sniffer for Windows. WinSniff is an application for capturing packets on the network. It displays all the packets that are transmitted on the local network and gives detailed information about each header in the packet. In order to keep it simple, I am not dealing with application level protocols. If you are interested, you can add features to support various application level protocols such as SMTP, FTP, NETBIOS etc
TFIND
searches for one or more strings (boolean AND) in a text file.
TFIND reports all lines where the string(s) were found (or NOT found
by option).
The search can be limited to a field in a fixed field (i.e. column
oriented) list.
An extended search mode is available, where only letters and digits
are relevant.
Other options:
case sensitive search,
alternative errorlevel with number of hits,
header line with file name, LFN, custom prefix
CHAPT12\Chapt12.cpp Part of the 32-bit test progrma for the Win32Port class.
CHAPT12\Chapt12.dsp The Visual C++ project file for the program.
CHAPT12\Chapt12.dsw The Visual C++ workspace file for the program.
CHAPT12\Chapt12.h The header file for the app s application class
CHAPT12\Chapt12.ico The icon used in Chapt12.exe
CHAPT12\Chapt12.rc The resource file use in the test program.
CHAPT12\Chapt12Dlg.cpp The implementation of the dialog class
CHAPT12\Chapt12Dlg.h The declarations of the dialog class
CHAPT12\MyWin32Port.h Definition for a class derived from Win32Port.
CHAPT12\resource.h The resource IDs
On-Line MCMC Bayesian Model Selection
This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
