The Mathematics of Coding Theory, 1st Edition by Paul Garrett

By Paul Garrett

This publication makes a truly obtainable creation to a vital modern software of quantity thought, summary algebra, and likelihood. It comprises various computational examples all through, giving beginners the chance to use, perform, and fee their knowing of key techniques. KEY subject matters assurance begins from scratch in treating likelihood, entropy, compression, Shannon¿s theorems, cyclic redundancy tests, and error-correction. For fanatics of summary algebra and quantity thought.

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The Mathematics of Coding Theory, 1st Edition

This booklet makes a truly obtainable advent to a crucial modern software of quantity idea, summary algebra, and likelihood. It comprises various computational examples all through, giving beginners the chance to use, perform, and money their figuring out of key recommendations. KEY themes assurance starts off from scratch in treating chance, entropy, compression, Shannon¿s theorems, cyclic redundancy tests, and error-correction.

Additional resources for The Mathematics of Coding Theory, 1st Edition

Example text

For any permutation i -+ s(i) of the indices, • • That is, only the probabilities matter, not their ordering or labeling. H(pl. ,Pn) ~ 0, and is 0 only if one of the PiS is 1. That is, uncertainty disappears entirely only if there is no randomness present. H(pl. ,Pn) = H(pl. ,Pn, 0). That is, 'impossible' outcomes do not contribute to uncertainty. • 1 1 1 1 H(-, ... -.. n • • ' . ' n+l That is, a larger ensemble of equally likely possibilities is more uncertain than a smaller ensemble. H should be a continuous function of the probabilities: 'small' changes in the probabilities should not cause 'large' changes in uncertainty.

What 'concise' means here is that it lacks redundancy (meaning that it does not repeat itself). Equivalently, there is a high information rate. Looking at the somewhat lower-level structure of language: most isolated typographical errors in ordinary text are not hard to correct. This is because of the redundancy of natural languages such as English. For example, The sun was shining brghtly. is easy to correct to The sun was shining brightly. In fact, in this particular example, the modifier 'brightly' is hardly necessary at all: the content would be almost identical if the word were omitted entirely.

Exaegiment and paryern rectgrikion aoj imuovtant en thmbyr theory. Expedimctt anc kat cern recagnition rre impertant in numbzr theory. In these 10 examples few of the words are recognizable. That is, looking for an English word whose spelling is close to the given, presumably misspelled, word does not succeed on a majority of the words in these garbled fragments. This is because so many letters have been changed that there are too many equally plausible possibilities for correction. Even using semantic information, these sentences are mostly too garbled to allow recovery of the message.

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