1 Data Compression Systems -- 1.1 Why compression? -- 1.2 Fundamental operations -- 1.3 Terminology -- 1.4 Related material -- 1.5 Analysis of algorithms -- 2 Fundamental Limits -- 2.1 Information content -- 2.2 Kraft inequality -- 2.3 Human compression -- 2.4 Mechanical compression systems -- 3 Static Codes -- 3.1  Unary and binary codes -- 3.2 Elias codes -- 3.3  Golomb and Rice codes -- 3.4 Interpolative coding -- 3.5 Making a choice -- 4 Minimum-Redundancy Coding -- 4.1  Shannon-Fano codes -- 4.2 Huffman coding -- 4.3  Canonical codes -- 4.4 Other decoding methods -- 4.5 Implementing Huffman's algorithm -- 4.6 Natural probability distributions -- 4.7 Artificial probability distributions -- 4.8 Doing the housekeeping chores -- 4.9 Related material -- 5 Arithmetic Coding -- 5.1  Origins of arithmetic coding -- 5.2 Overview of arithmetic coding -- 5.3 Implementation of arithmetic coding -- 5.4 Variations -- 5.5 Binary arithmetic coding -- 5.6 Approximate arithmetic coding -- 5.7 Table-driven arithmetic coding -- 5.8 Related material -- 6 Adaptive Coding -- 6.1  Static and semi-static probability estimation -- 6.2 Adaptive probability estimation -- 6.3 Coping with novel symbols -- 6.4 Adaptive Huffman coding -- 6.5 Adaptive arithmetic coding -- 6.6 Maintaining cumulative statistics -- 6.7 Recency transformations -- 6.8 Splay tree coding -- 6.9 Structured arithmetic coding -- 6.10 Pseudo-adaptive coding -- 6.11 The Q-coder -- 6.12 Making a choice -- 7 Additional Constraints -- 7.1 Length-limited coding -- 7.2 Alphabetic coding -- 7.3 Alternative channel alphabets -- 7.4 Related material -- 8 Compression Systems -- 8.1  Sliding window compression -- 8.2 Prediction by partial matching -- 8.3 Burrows-Wheeler transform -- 8.4 Other compression systems -- 8.5 Lossy modeling -- 9 What Next? -- References.