Theory of Quantization and Synchronization with Timing

虽然储存和传输信息的成本继续下降，但这种减少似乎只是刺激了对信息的需求，从而促进了数据压缩的进一步发展。这项研究的第一个目标是推动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、视频和音乐等来源。同步是在以下环境中操作的数据压缩系统中的关键问题：解码可能在压缩比特流中的任意点开始，或者其中压缩流可能因插入、删除或替换错误而被破坏。这项研究的第二个目标是开发一种数据同步理论，该理论考虑到用户需要知道数据的时间指标及其值。即将开发的量化理论将增加对有损压缩系统性能与其复杂性之间关系的定性和定量理解，从而能够设计出更好的系统。方法论在很大程度上但不完全基于高分辨率的理论、技术和概念。主要集中在矢量量化，作为一种实用技术和研究基本问题的范例。尽管同步方法已经得到了很大的发展，但还没有理论来分析和设计同步码，除了允许解码器与编码器同步之外，还使其能够产生对其解码的数据的时间索引的估计。这项研究将发展这样的理论。它将专注于优化编码效率(速率)、再同步延迟和定时信息产生之间的权衡。还将研究对具有插入、删除和替换错误的通道进行编码的这种方法的应用。

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.