Theory of Quantization and Synchronization with Timing

量化和定时同步理论

• 批准号: 9815006
• 负责人: David Neuhoff
• 金额: $ 34.02万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-08-01 至 2003-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9815006&HistoricalAwards=false
• 关键词: Theory; Quantization; Synchronization; Timing

Though the cost of storing and transmitting information continues to decrease, such reductions seem only to stimulate demand for information and, consequently, for further developments in data compression. The first goal of this research is to advance the theory and practice of quantization as a lossy data compression methodology, for sources such as speech, images, video and music. Synchronization is a key issue in data compression systems that operate in environments where decoding may begin at an arbitrary point in the compressed stream of bits, or where the compressed stream may be corrupted by insertion, deletion or substitution errors. The second goal of this research is to develop a theory of data synchronizationthat takes into account the users need to know the time indices of the data, as well as its values.The quantization theory to be developed will increase the qualitative and quantitative understanding of how the performance of lossy compression systems relates to their complexity, with the goal of enabling better systems to be designed. The methodology is largely, but not exclusively, based on high resolution theory techniques and concepts. The focus is primarily on vector quantization, both as a practical technique and as a paradigm for studying fundamental issues.Though synchronization methods have been much developed, there is no theory for the analysis and design of synchronization codes that, in addition to permitting the decoder to synchronize with the encoder, enable it to produce estimates of the time indices of the data it decodes. This research will develop such a theory. It will focus on optimizing the tradeoffs among coding efficiency (rate), resynchronization delay, and the production of timing information. The application of such methods to coding for channels with insertion, deletion and substitution errors will also be investigated.

虽然存储和传输信息的成本不断降低，但这种降低似乎只会刺激对信息的需求，从而促进数据压缩的进一步发展。 本研究的第一个目标是推进量化作为一种有损数据压缩方法的理论和实践，用于语音，图像，视频和音乐等源。 同步是数据压缩系统中的一个关键问题，该系统工作在解码可能在压缩比特流中的任意点开始开始的环境中，或者压缩流可能被插入、删除或替换错误破坏的环境中。 本研究的第二个目标是发展一种数据同步的理论，它考虑到用户需要知道数据的时间索引，以及它的values.The量化理论的发展将增加定性和定量的了解如何有损压缩系统的性能与它们的复杂性，使更好的系统设计的目标。 该方法在很大程度上，但不完全是基于高分辨率的理论技术和概念。 重点主要是矢量量化，既作为一种实用的技术，也作为一种研究基本问题的范例。虽然同步方法已经得到了很大的发展，但除了允许解码器与编码器同步之外，还没有同步码的分析和设计理论，使其能够产生它解码的数据的时间索引的估计。 这项研究将发展这样一种理论。 它将专注于优化编码效率（速率），解码延迟和定时信息的产生之间的权衡。 这种方法的应用编码的插入，删除和替换错误的通道也将进行调查。