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Background on Information Theory and Coding Theory

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Selected Unsolved Problems in Coding Theory

Part of the book series: Applied and Numerical Harmonic Analysis ((ANHA))

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Abstract

This chapter summarizing background information assumes that the reader has some familiarity with linear algebra and basic probability. The basic model of information theory and error-correcting block codes is introduced. The basic example of the Hamming [7,4,3] code is presented in detail.

What is ironic is that even in basic background issues, coding theory has interesting open questions. For example, for a given length and dimension, which code is the best 2-error-correcting code? Another example: see Manin’s theorem 19 and the closely related Conjecture 22 below.

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Notes

  1. 1.

    From the publication point of view, Hamming published only binary [7,4,3] code, and Golay published the other binary and nonbinary Hamming codes. However it has been shown that Hamming knew all the binary codes prior to Shannon’s publication and had circulated them in an interdepartmental memorandum several months prior to the submission date of Golay’s one-page paper [Tho].

  2. 2.

    Here “GF” stands for Galois field, named after the French mathematician Evariste Galois who died after a duel at the age of 20. See http://en.wikipedia.org/wiki/Evariste_Galois for more details on his life’s story.

  3. 3.

    In other words, add the entries placed in each circle mod 2. If this sum is \(\equiv1\pmod{2}\), then we say that the circle fails the parity check; otherwise, it passes. See Example 5.

  4. 4.

    The appendix Sect. 7.2 gives further details on finite fields.

  5. 5.

    “Short exact” means (a) the arrow G is injective, i.e., G is a full-rank k×n matrix, (b) the arrow H is surjective, and (c) image(G)=kernel(H).

  6. 6.

    If e>1 is allowed to vary with n, then more can be said, but we omit that case.

  7. 7.

    Although, please see Chap. 4, where some interesting but conjectural results use quadratic residue code-like constructions to find related codes which might have very good parameters.

  8. 8.

    We follow [MS], Sects. 16.4–16.5.

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Joyner, D., Kim, JL. (2011). Background on Information Theory and Coding Theory. In: Selected Unsolved Problems in Coding Theory. Applied and Numerical Harmonic Analysis. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-0-8176-8256-9_1

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