In recent years large scientific interest has been devoted to joint data decoding and parameter estimation techniques. In this paper, iterative turbo decoding joint to channel frequency and phase estimation is proposed. The phase and frequency estimator is embedded into the structure of the turbo decoder itself, taking into consideration both turbo interleaving and puncturing. Results show that the proposed technique outperforms conventional approaches both in terms of detection capabilities and implementation complexity.
標(biāo)簽： scientific parameter interest decoding
上傳時(shí)間： 2015-12-30
上傳用戶：894898248
data Structures with C++附代碼
標(biāo)簽： Structures data with 代碼
上傳時(shí)間： 2014-01-27
上傳用戶：trepb001
Techniques for storing and processing data are at the heart of all programs. The term data structure is used to describe the way data is stored, and the term algorithm is used to describe the way data is processed.
標(biāo)簽： data Techniques processing structure
上傳時(shí)間： 2014-03-10
上傳用戶：cc1
VESA Display Device data Block (DDDB) Standard Display Device data Block This proposal defines the Display Device data Block (DDDB), for use in a CEA-861-compatible EDID extension, as originally proposed in the VESA TV Compatibility White Paper (Compatibility of PC and CE Displays, Aug.1, 2005).
標(biāo)簽： Display Device Block data
上傳時(shí)間： 2014-10-11
上傳用戶：wanghui2438
VESA Display Transfer Characteristics data Block Standard Display Transfer Characteristics data Block
標(biāo)簽： Characteristics Transfer Display data
上傳時(shí)間： 2016-01-01
上傳用戶：Thuan
VESA VIDEO TIMING BLOCK EXTENSION data STANDARD VTB-EXT Standard 求edid2.0
標(biāo)簽： EXTENSION STANDARD Standard VTB-EXT
上傳時(shí)間： 2014-12-05
上傳用戶：wpwpwlxwlx
ADO.NET 2.0 SQLite data Provider, 用于在.NET 中調(diào)用嵌入式SQLITE 數(shù)據(jù)庫。支持Visual Studio 2005 界面中的數(shù)據(jù)庫設(shè)計(jì)
標(biāo)簽： NET Provider SQLite SQLITE
上傳時(shí)間： 2014-12-06
上傳用戶：duoshen1989
ADO.NET 2.0 SQLite data Provider開發(fā)工具的C# 源代碼，可用于學(xué)習(xí)借鑒C#編程之用。
標(biāo)簽： Provider SQLite data ADO
上傳時(shí)間： 2014-01-26
上傳用戶：xiaoyunyun
The need for accurate monitoring and analysis of sequential data arises in many scientic, industrial and nancial problems. Although the Kalman lter is effective in the linear-Gaussian case, new methods of dealing with sequential data are required with non-standard models. Recently, there has been renewed interest in simulation-based techniques. The basic idea behind these techniques is that the current state of knowledge is encapsulated in a representative sample from the appropriate posterior distribution. As time goes on, the sample evolves and adapts recursively in accordance with newly acquired data. We give a critical review of recent developments, by reference to oil well monitoring, ion channel monitoring and tracking problems, and propose some alternative algorithms that avoid the weaknesses of the current methods.
標(biāo)簽： monitoring sequential industria accurate
上傳時(shí)間： 2013-12-17
上傳用戶：familiarsmile
DVB specification for data broadcasting
標(biāo)簽： specification broadcasting data DVB
上傳時(shí)間： 2016-01-03
上傳用戶：q123321
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