Seibt Algorithmic Information Theory

Mathematics of Digital Information Processing
1. Auflage 2007
ISBN: 978-3-540-33219-0
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 443 Seiten

Algorithmic Information Theory treats the mathematics of many important areas in digital information processing. It has been written as a read-and-learn book on concrete mathematics, for teachers, students and practitioners in electronic engineering, computer science and mathematics. The presentation is dense, and the examples and exercises are numerous. It is based on lectures on information technology (Data Compaction, Cryptography, Polynomial Coding) for engineers.

Autoren/Hrsg.

Seibt, Peter

Inhaltsverzeichnis

1;Contents;6
2;Introduction;8
3;1 Data Compaction;12
3.1;1.1 Entropy Coding;12
3.2;1.2 Universal Codes: The Example LZW;50
4;2 Cryptography;56
4.1;2.1 The Data Encryption Standard;57
4.2;2.2 The Advanced Encryption Standard: The Cipher Rijndael;67
4.3;2.3 The Public Key Paradigm and the Cryptosystem RSA;100
4.4;2.4 Digital Signatures;108
5;3 Information Theory and Signal Theory: Sampling and Reconstruction;178
5.1;3.1 The Discrete Fourier Transform;179
5.2;3.2 Trigonometric Interpolation;197
5.3;3.3 The Whittaker–Shannon Theorem;205
6;4 Error Control Codes;228
6.1;4.1 The Reed–Solomon Codes;228
6.2;4.2 Convolutional Codes;246
7;5 Data Reduction: Lossy Compression;274
7.1;5.1 DFT, Passband Filtering and Digital Filtering;275
7.2;5.2 The Discrete Cosine Transform;281
7.3;5.3 Filter Banks and Discrete Wavelet Transform;321
8;References;442
9;Index;446