ITR: Universal Discrete Denoising

ITR：通用离散去噪

• 批准号: 0312839
• 负责人: Sergio Verdu
• 金额: $ 21万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0312839&HistoricalAwards=false
• 关键词: ITR; Universal; Discrete; Denoising

ABSTRACT0312839Verdu, SergioPrinceton UIn this proposal we describe an integrated research program on a new research area with a very richarray of applications: the problem of .ltering or denoising of discrete sequences. This statisticalsignal processing problem arises naturally in a wide range of applications spanning a variety ofinformation technology applications in .elds as varied as computer science, statistics, engineering,astronomy, biology, and information theory.Consider the problem of recovering a signal from a noisy version, which has been corruptedby a known channel. The recovery can assume two major modes depending on the application:noncausal, i.e. it starts once the entire signal is available;and causal, i.e. decisions must be madeimmediately after each symbol is received.The continuous case, where the input and output alphabets are the real line (or other Euclideanspaces), has received immeasurable attention for over half a century, as witnessed by major contributionsto linear .ltering by Wiener, Kolmogorov and Kalman, and to nonlinear .ltering byDonoho and Johnstone.

本文介绍了一个综合研究计划，它涉及一个新的应用领域：离散序列的滤波或去噪问题。这个复杂的信号处理问题自然会出现在广泛的应用中，这些应用涵盖了计算机科学、统计学、工程学、天文学、生物学和信息论等领域的各种信息技术应用。考虑从被已知信道破坏的噪声信号中恢复信号的问题。根据应用，恢复可以采用两种主要模式：非因果模式，即一旦整个信号可用，它就开始;因果关系，即在接收到每个符号后必须立即作出决定。连续情况，输入和输出字母是真实的行（或其他欧几里德空间），已经收到了不可估量的关注超过半个世纪，正如见证的主要贡献线性。ltering由维纳，柯尔莫哥洛夫和卡尔曼，Donoho和Johnstone的非线性滤波。