CAREER: Toward a Unified Approach to Universality in Information Processing

职业：走向信息处理通用性的统一方法

• 批准号: 0546535
• 负责人: Tsachy Weissman
• 金额: $ 40万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-03-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0546535&HistoricalAwards=false
• 关键词: CAREER; Toward; Unified; Approach; Universality

A major challenge in signal processing, communication, and compression applications is the construction of schemes that approach the theoretical performance limits. The fact that a priori knowledge of source and channel characteristics is rarely available in practice necessitates that these schemes be universal. While it is clear that existing universal schemes for different problems share many common ingredients, thus far they have been considered mostly separately. This project develops a unified framework encompassing theoretical, algorithmic, and implementation aspects of the universality problem.We address questions concerning universal schemes in problem areas ranging from denoising, Wyner-Ziv coding, joint source-channel coding, scanning and prediction, to reinforcement learning. We develop a unified framework for addressing such questions, which facilitates the construction of universal schemes for new problems, and leads to new insights on existing ones. On the more applied side, we are developing new algorithmic paradigms that have attractive complexity, and applying them in practice. We are also developing analytic tools for assessing the performance of the new algorithms.

信号处理、通信和压缩应用中的一个主要挑战是构建接近理论性能极限的方案。信源和信道特性的先验知识在实践中很少可用，这一事实使得这些方案必须是通用的。虽然现有的针对不同问题的通用方案显然有许多共同之处，但到目前为止，它们大多是分开考虑的。这个项目开发了一个统一的框架，包括普适性问题的理论、算法和实现方面。我们解决了从去噪、Wyner-Ziv编码、联合信源-信道编码、扫描和预测到强化学习等问题领域中关于通用方案的问题。我们为解决这些问题制定了一个统一的框架，这有助于为新问题构建通用方案，并导致对现有问题的新见解。在更实用的方面，我们正在开发具有诱人复杂性的新算法范例，并将它们应用于实践。我们还在开发分析工具，以评估新算法的性能。