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This book focuses on information processing rather than information theory, which typically involves description and estimation. It presents a unique perspective, initially developed through lectures on “Information theory, through the looking-glass of an algebraist.” Over time, the material has evolved, maintaining a strong algebraic theme that intertwines polynomial and matrix algebra within signal theory. A solid grasp of elementary arithmetic and Linear Algebra is essential for understanding the algorithms explored in various bit-stream landscapes. The emphasis on algebra serves as the backbone of the discussion. The book is structured into five chapters of increasing complexity, each addressing distinct topics in Discrete Mathematics. The first two chapters cover data compaction (lossless data compression) and cryptography, aimed at an undergraduate audience. The primary mathematical prerequisite is a solid understanding of quotient rings, particularly finite fields, predominantly in characteristic 2. This approach ensures that readers are well-equipped to engage with the material, reinforcing the importance of algebra in the study of information processing.
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Algorithmic information theory, Peter Seibt
- Langue
- Année de publication
- 2006
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