: Peter Seibt
: Algorithmic Information Theory Mathematics of Digital Information Processing
: Springer-Verlag
: 9783540332190
: 1
: CHF 115.70
:
: Grundlagen
: English
: 443
: Wasserzeichen/DRM
: PC/MAC/eReader/Tablet
: PDF

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.

Contents6
Introduction8
1 Data Compaction12
1.1 Entropy Coding12
1.2 Universal Codes: The Example LZW50
2 Cryptography56
2.1 The Data Encryption Standard57
2.2 The Advanced Encryption Standard: The Cipher Rijndael67
2.3 The Public Key Paradigm and the Cryptosystem RSA100
2.4 Digital Signatures108
3 Information Theory and Signal Theory: Sampling and Reconstruction178
3.1 The Discrete Fourier Transform179
3.2 Trigonometric Interpolation197
3.3 The Whittaker–Shannon Theorem205
4 Error Control Codes228
4.1 The Reed–Solomon Codes228
4.2 Convolutional Codes246
5 Data Reduction: Lossy Compression274
5.1 DFT, Passband Filtering and Digital Filtering275
5.2 The Discrete Cosine Transform281
5.3 Filter Banks and Discrete Wavelet Transform321
References442
Index446