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Sinopsis
This text is an introduction to the subjects of information and coding theory at the graduate or advanced undergraduate level. It assumes a basic knowledge of probability and linear algebra, but is otherwise self-contained. The first quarter of the book is devoted to the basics of information theory, including a proof of Shannon's famous Noisy Coding Theorem. The remainder of the book is devoted to coding theory and has a decidedly algebraic flavour. After a brief discussion of general families of codes, the authors discuss linear codes, (including the Hamming, Golay, and Reed-Miller codes), finite fields and cyclic codes. An appendix reviews relevant topics from modern algebra.
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Reseña del editor
This text is an introduction to the subjects of information and coding theory at the graduate or advanced undergraduate level. It assumes a basic knowledge of probability and linear algebra, but is otherwise self-contained. The first quarter of the book is devoted to the basics of information theory, including a proof of Shannon's famous Noisy Coding Theorem. The remainder of the book is devoted to coding theory and has a decidedly algebraic flavour. After a brief discussion of general families of codes, the authors discuss linear codes, (including the Hamming, Golay, and Reed-Miller codes), finite fields and cyclic codes. An appendix reviews relevant topics from modern algebra.
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