We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems.We study the performance of a standard CFO estimate, which consists of first raising the received signal to the Mth power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of samples required in the CFO estimation procedure, in Order to ensure that the MSE on estimation is not significantly affected by the outliers.
標簽： frequency-offset estimation quadrature amplitude
上傳時間： 2014-01-22
上傳用戶：牛布牛
In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed.We showin particular how to incorporate local linearisation methods similar to those which have previously been employed in the deterministic filtering literature these lead to very effective importance distributions. Furthermore we describe a method which uses Rao-Blackwellisation in Order to take advantage of the analytic structure present in some important classes of state-space models. In a final section we develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.
標簽： sequential simulation posterior overview
上傳時間： 2015-12-31
上傳用戶：225588
This library provides a C++ interface to XML files. It uses libxml 2 to access the XML files, and in Order to configure libxml++ you must have both libxml and pkg-config installed.
標簽： files interface XML provides
上傳時間： 2016-01-05
上傳用戶：firstbyte
radius協議源碼÷The Radius Stack will connect to a Radius Server. This stack implementation is built upon the UdpStack which is available in the radius{version}/util directory. A minimal set of VSAs (Vendor Specific Attributes are supported by this stack). The Radius Stack should be used as a base class. In Order to implement a larger set of VSAs, one will need to subclass from the Radius Stack and implement the functionality within the virtual function processVsa(). The Radius Stack supports mostly accounting messages. The authentcation messages will be supported in a future release. A test program has been provided in the radius directory. This program shows how to subclass from the RadiusStack and how to use the api.
標簽： Radius implementation connect radius
上傳時間： 2013-12-12
上傳用戶：壞天使kk
We have a group of N items (represented by integers from 1 to N), and we know that there is some total Order defined for these items. You may assume that no two elements will be equal (for all a, b: a<b or b<a). However, it is expensive to compare two items. Your task is to make a number of comparisons, and then output the sorted Order. The cost of determining if a < b is given by the bth integer of element a of costs (space delimited), which is the same as the ath integer of element b. Naturally, you will be judged on the total cost of the comparisons you make before outputting the sorted Order. If your Order is incorrect, you will receive a 0. Otherwise, your score will be opt/cost, where opt is the best cost anyone has achieved and cost is the total cost of the comparisons you make (so your score for a test case will be between 0 and 1). Your score for the problem will simply be the sum of your scores for the individual test cases.
標簽： represented integers group items
上傳時間： 2016-01-17
上傳用戶：jeffery
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
標簽： application describes capturing for
上傳時間： 2016-01-22
上傳用戶：lijianyu172
You imagine? Right, there s more than one possibility, this time I ll give you tree. One for your private data, one for the common data in Order to receive data from other applications like Excel, WinWord etc. and at last, I ll give you a handy-dandy class you can derive ANY MFC object from, to make it a drop target
標簽： possibility imagine Right there
上傳時間： 2013-12-21
上傳用戶：jichenxi0730
aDABOOST This package contains the following files: learner.jar - is a platform independent java package. In Order to run it on windows/linux open the command prompt/shell and type the command "java -jar learner.jar". Make sure the java installation path is set in the system enviroment. learner.exe - A windows executable version of the application. Doubleclick to run. learner.pdf - The digital version of the report. SRC\ - The source code of the program is in this directory
標簽： independent following aDABOOST contains
上傳時間： 2014-12-05
上傳用戶：xsnjzljj
OpenSVM was developped under Visual C++ 6.0 SP6, You can open the workspace file(*.dsw) in the opensvm-src folder. The folder include the svm.h and svm.cpp which in the libsvm (Copyright (c) 2000-2007 Chih-Chung Chang and Chih-Jen Lin All rights reserved) in the opensvm-src\libsvm. However, the files svm.h and svm.cpp codes were copied/merged into stdafx.h and stdafx.cpp in Order to support the development, and OpenSVM still use other codes of libsvm. So you can see the libsvm package in the source package. You can open and build it with Visual C++ 6.0. Note: the problems must be in LIBSVM format. OpenSVM project page: http://sourceforge.net/projects/opensvm If you had any question, please mail to: cloudbyron@gmail.com
標簽： developped the workspace OpenSVM
上傳時間： 2016-01-30
上傳用戶：asdfasdfd
Using Gaussian elimination to solve linear equations. // In this version, we allow matrix of any size. This is done by treating // the name of a 2-dimensional array as pointer to the beginning of the // array. This makes use of the fact that arrays in C are stored in // row-major Order.
標簽： elimination equations Gaussian version
上傳時間： 2016-02-14
上傳用戶：hxy200501
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