CIF: Small: Collaborative Research: Combinatorial Joint Source-Channel Coding

CIF：小型：协作研究：组合联合源通道编码

• 批准号: 1318620
• 负责人: Yury Polyanskiy
• 金额: $ 25万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1318620&HistoricalAwards=false
• 关键词: CIF; Small; Collaborative; Research; Combinatorial

Algorithms for lossy/lossless compression and error-correcting codes have been at the core of the digital revolution. This project focuses on the particular set of applications in which both lossy compression and noise resilience are required. Examples include storage of high resolution imagery on non-perfect semiconductor (flash) memory and real-time video surveillance over jammed or noisy channels.The state-of-the art solution is "separation": serial concatenation of an off-the-shelf compression algorithm with an off-the-shelf error-correcting code. However, as shown recently by the investigators, for worst-case guarantees the separated solution is far from being (even asymptotically) optimal. This provides the principal motivation for a multifaceted investigation of the combinatorial, geometric, algebraic and information theoretic aspects of the joint source-channel coding problem.The breadth of mathematics will be appealing to young researchers with a wide variety of backgrounds, and will help attract new talent to the field. Creation of sophisticated source-channel codes with dependable guarantees is expected to have technological impact in military, space exploration, natural science, and consumer applications.

有损/无损压缩算法和纠错码一直是数字革命的核心。这个项目的重点是在有损压缩和噪声弹性都需要特定的应用程序集。例子包括在非完美半导体（闪存）存储器上存储高分辨率图像，以及在堵塞或噪声信道上进行实时视频监控。最先进的解决方案是“分离”：将现成的压缩算法与现成的纠错码串行连接。然而，正如最近的研究人员所示，对于最坏情况的保证，分离的解决方案远远不是（甚至是渐近）最优的。这为联合信源信道编码问题的组合、几何、代数和信息论方面的多方面研究提供了主要动力。数学的广度将吸引具有各种背景的年轻研究人员，并将有助于吸引新的人才进入该领域。具有可靠保证的复杂源信道码的创建预计将在军事，空间探索，自然科学和消费应用中产生技术影响。