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

职业：通用数据压缩的进展及其在联合源和通道编码中的应用

• 批准号: 0347969
• 负责人: Gil Shamir
• 金额: $ 40.06万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-12-15 至 2010-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0347969&HistoricalAwards=false
• 关键词: CAREER; Advances; Universal; Data; Compression

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.

这项研究的目的是开发几个未开发的INDATA压缩区域，并在其他应用中使用通用数据压缩技术，包括生物建模和联合源通道编码的通向方向。 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当源统计量被启用时，从不良渠道条件下的源性同步问题解决了普遍性问题。 这项研究开发了对抗问题的技术，甚至在冗余通道信息流的通道解码强度中获得了“自由”增益。公共压迫方案假设数据来自已知的字母，它具有“标准”固定或不断变化的模型，并且由长序列组成。但是，（a）存在具有较大未知数的压缩应用，例如文本压缩，其中构成thealphabet的文本压缩，（b）大多数真实的数据序列通常既不是不断变化的统计量的固定性，也不是在大型压缩数据库中进行随机访问。研究人员Studiesthese三个非传统问题。研究工作结合了严格的理论结果的开发，包括列出和描述长度界限，经验测试，算法设计，侧重于实用的低复杂技术以及对拟议技术的实施。最后，该研究还研究了通用压缩技术对生物序列的分割和建模的使用。