explain how to open the Waveform Viewer for Verification
? State how to insert nodes into the Waveform Viewer
? Tell how to assign Stimulus with the Stimulator Selector
Windowed-Burg method is made in order to improve the Clasical Burg method. Previously, I send the PBURGW.m file, but now I include also the ARBURGW.m algorithm and some NOTES-EXAMPLES to explain it and compare with the pburg.m algorithm from MATLAB.
this file turber_code.rar have two file,file STBC.h is parameter,file STBC.cpp is computer.file STBC.cpp has very clean chinese explain
,so you can easy understand
We often get questions about how the deflate() and inflate() functions should be used. Users wonder when they should provide more input, when they should use more output, what to do with a Z_BUF_ERROR, how to make sure the process terminates properly, and so on. So for those who have read zlib.h (a few times), and would like further edification, below is an annotated example in C of simple routines to compress and decompress from an input file to an output file using deflate() and inflate() respectively. The annotations are interspersed between lines of the code. So please read between the lines. We hope this helps explain some of the intricacies of zlib.
Zlib函數列表 We often get questions about how the deflate() and inflate() functions should be used. Users wonder when they should provide more input, when they should use more output, what to do with a Z_BUF_ERROR, how to make sure the process terminates properly, and so on. So for those who have read zlib.h (a few times), and would like further edification, below is an annotated example in C of simple routines to compress and decompress from an input file to an output file using deflate() and inflate() respectively. The annotations are interspersed between lines of the code. So please read between the lines. We hope this helps explain some of the intricacies of zlib.
Developers use algorithms and data structures every day of their working lives. Having a good under-standing of these algorithms and knowledge of when to apply them is essential to producing softwarethat not only works correctly, but also performs efficiently.
This book aims to explain those algorithms and data structures most commonly encountered in day-to-day software development, while remaining at all times practical, concise, and to the point, with little orno verbiage to distract from the core concepts and examples.
This Source.zip has three application code folders containing .java and .class files and two .jar files as follows:
1. desktop-side_JXTA4JMS
2. mobile-side_JXTA4JMS
3. JMS Test Client
4. Listener.jar
5. JMSTestClient.jar
We now explain execution steps, we followed, to run this JXTA4JMS application.
Before we try we require Application softwares and need to configure JXTA relay and J2EE server.
印度高手Struts and Hibernate教程,用MyEclipse開發.書和源碼In this tutorial we will show how the Web Framework Struts and the Database Persistence Solution
Hibernate can be used together. Though we explain some basic, you should try the basic tutorials
for each technology first when you are a beginner.
Visual C++
Windows Shell Programming
Welcome to Visual C++ Windows Shell Programming! With this book, you ll learn how to program the
Windows Shell, customize its behavior and integrate your applications with it. You ll discover how to
use and modify its features to best effect, and the way to call shell API functions whose
documentation is scant. Programming the shell isn t difficult, but few books explain the subject in its
entirety.
The algorm of viterbi. You talk to your friend three days in a row and discover that on the first day he went for a walk, on the second day he went shopping, and on the third day he cleaned his apartment. You have two questions: What is the overall probability of this sequence of observations? And what is the most likely sequence of rainy/sunny days that would explain these observations? The first question is answered by the forward algorithm the second question is answered by the Viterbi algorithm. These two algorithms are structurally so similar (in fact, they are both instances of the same abstract algorithm) that they can be implemented in a single function:
