Turbo Like Codes for Distributed Source and Joint Source-Channel Coding of Correlated Sources
Turbo Like Codes for Distributed Source and Joint Source-Channel Coding of Correlated Sources
批准号:
0311014
负责人:
Javier Garcia-Frias
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-07-15 至 2008-06-30
中文摘要
0311014特拉华大学的Javier Garcia-FriasU这项研究涉及对由多个源传输相关信息组成的通信系统的研究。最后的目标是利用源之间的相关性来减少总的传输能量。在这项研究中开发的技术可能会在传感器网络领域产生广泛的影响,使人们有可能开发需要更少的传输功率的传感器。 为了降低传输的总能量,本研究将集中于Turbo类编码的应用,特别是具有低密度生成矩阵的线性编码的应用,以i)对于广泛的多端相关源实现接近理论极限的压缩率(离散的或连续的,有或没有存储器)和ii)对大范围的多终端相关信源和不同信道环境执行联合信源信道编码。所提出的系统的特点是其简单的编码器的网站。这种简单性有利于在实际应用中实现所提出的方案。此外,编码过程对于每个源是完全独立的,并且它不需要关于相关模型或源统计的知识,这在诸如传感器网络和图像/视频压缩的实际应用中是非常感兴趣的。为了达到接近信源和联合信源信道编码的理论极限的性能,信源的统计信息在解码器处以自适应的方式被估计和利用。
英文摘要
0311014Javier Garcia-FriasU of DelawareThis research involves the study of communications systems consisting of multiple sources transmitting correlated information. The final objective is to exploit the correlation among the sources to reducethe total transmitted energy. The techniques developed in this research may have a broad impact in the area of sensor networks, making it possible to develop sensors requiring less transmitted power. For example, a possible applications could be the development of less-power-invasive biosensors.In order to reduce the total transmitted energy, the research will focus on the application of turbo-like codes, and specifically of linear codes with low-density generator matrix to i) achieve compression rates close to theoretical limits for a wide range of multi-terminal correlated sources (discrete or continuous, with and without memory) and ii) perform joint source-channel coding for a wide range of multi-terminal correlated sources and different channel environments. The proposed system is characterized by its simplicity at the encoder site. This simplicity facilitates the implementation of the proposed scheme in practicalapplications. Moreover, the encoding process is completely independent for each source, and it does not require knowledge about the correlation model or source statistics, which is of great interest in practicalapplications such as sensor networks and image/video compression. In order to achieve a performance close to the theoretical limits for source and joint source-channel coding, the statistics of the sourcesare estimated and exploited at the decoder in an adaptive fashion.
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Collaborative Research: CIF: Small: Beyond Compressed Sensing: Analog Coding for Communications
-
批准号:2007754
-
项目类别:Standard Grant
-
资助金额:$27.0万
-
财政年份:2020
-
负责人:Javier Garcia-Frias
-
依托单位:
FET: CIF: Small: Graph-Based Quantum Error Correcting Codes
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批准号:2007689
-
项目类别:Standard Grant
-
资助金额:$50.0万
-
财政年份:2020
-
负责人:Javier Garcia-Frias
-
依托单位:
CIF: Small: Hybrid analog-digital schemes for joint source-channel coding of digital sources
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批准号:1618653
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项目类别:Standard Grant
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资助金额:$40.32万
-
财政年份:2016
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负责人:Javier Garcia-Frias
-
依托单位:
CIF: Small: Non-Linear Processing and Coding for Compressive Sensing with Applications in Imaging
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批准号:0915800
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项目类别:Standard Grant
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资助金额:$50.0万
-
财政年份:2009
-
负责人:Javier Garcia-Frias
-
依托单位:
Exploiting Prior Knowledge in Compressed Sensing
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批准号:0725422
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项目类别:Standard Grant
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资助金额:$30.0万
-
财政年份:2007
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负责人:Javier Garcia-Frias
-
依托单位:
CAREER: Iterative Decoding Schemes For Channels With Memory: Application To Fading Channels
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批准号:0093215
-
项目类别:Continuing Grant
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资助金额:$0.0万
-
财政年份:2001
-
负责人:Javier Garcia-Frias
-
依托单位:
国内基金
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