CAREER:Advances in Universal Data Compression with Applications to Joint Source and Channel Coding

这项研究的目的是在数据压缩方面开发几个未被探索的领域，以及在其他应用中利用通用数据压缩技术，包括生物建模和信源-信道联合编码的新方向。研究集中在四个方面：(A)信源-信道联合通用信源编码编码的设计；(B)对大的和未知信源字母表的通用压缩的研究；(C)针对非传统但更现实的数据模型的高级通用编码技术的设计和实际实现；(D)随机接入无损压缩的研究。这项研究开发了解决这些问题的技术，甚至在冗余信道信息流的信道译码性能上获得“免费”的增益。常见的压缩方案假设数据来自已知的字母表，它有一个“标准的”固定的或不断变化的统计模型，并且它由一个长序列组成。然而，(A)存在具有大的未知字母的压缩应用，例如文本压缩，其中单词构成字母表，(B)大多数真实数据序列通常既不是静态的，也不是不断变化的统计的，以及(C)在大型压缩数据库中需要随机访问。调查者研究了这三个非传统问题。研究工作结合了严格的理论结果的发展，包括冗余度和描述长度界限，与经验测试，专注于实用的低复杂度技术的算法设计，以及所提出的技术的实现。最后，研究还探讨了使用通用压缩技术对生物序列进行分割和建模。

The purpose of this research is to develop several unexplored areas indata compression, as well as to utilize universal data compressiontechniques in other applications including biological modelling and anovel direction of joint source-channel coding. The research focuses onfour topics: (a) design of joint source-channel universal source codebased codes, (b) study of universal compression for large and unknownsource alphabets, (c) design of advanced universal coding techniques fornon-traditional, yet more realistic, data models with practicalimplementations, and (d) the study of random access lossless compression.Common techniques in joint source-channel coding suffer fromsevere synchronization problems in bad channel conditions and donot address universality issues when the source statistics areunknown. This research develops techniques to combat theseproblems, and even attain "free" gain in channel decodingperformance for redundant channel information streams. Commoncompression schemes assume that the data is from a known alphabet,it has a "standard" stationary or constantly changingstatistical model, and it consists of a long sequence. However,(a) there exist compression applications with large unknownalphabets, such as text compression where the words constitute thealphabet, (b) most real data sequences are usually neither stationarynor of constantly varying statistics, and (c) random access isnecessary in large compressed data bases. The investigator studiesthese three non-traditional problems. The research work combinesthe development of rigorous theoretical results includingredundancy and description length bounds, with empirical testing,algorithm design with focus on practical low-complexitytechniques, and implementation of proposed techniques. Finally,the research also investigates the use of universal compressiontechniques to segmentation and modelling of biological sequences.