Название: Information and coding theory in computer science
Автор: Zoran Gacovski
Издательство: Arcler Press
Год: 2023
Страниц: 416
Язык: английский
Формат: pdf (true)
Размер: 36.0 MB

This book covers different topics from information theory methods and approaches, block and stream coding, lossless data compression, and information and Shannon entropy. Section 1 focuses on information theory methods and approaches, describing information theory of cognitive radio system, information theory and entropies for quantized optical waves in complex time-varying media, some inequalities in information theory using Tsallis entropy, and computational theory of intelligence: information entropy. Section 2 focuses on block and stream coding, describing block-split array coding algorithm for long-stream data compression, bit-error aware lossless image compression with 2d-layer-block coding, beam pattern scanning (BPS) versus space-time block coding (STBC) and space-time trellis coding (STTC), partial feedback based orthogonal space-time block coding with flexible feedback bits, and rate-less space-time block codes for 5G wireless communication systems. Section 3 focuses on lossless data compression, describing lossless image compression technique using combination methods, new results in perceptually lossless compression of hyperspectral images, lossless compression of digital mammography using base switching method, and lossless image compression based on multiple-tables arithmetic coding. Section 4 focuses on information and Shannon entropy, describing entropy as universal concept in sciences, Shannon entropy - axiomatic characterization and application, Shannon entropy in distributed scientific calculations on mobiles ad-hoc networks (MANETs), the computational theory of intelligence: information entropy, and advancing Shannon entropy for measuring diversity in systems.