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Polar Codes I

Talkat Information Theory Boot Camp 2015 · 2015-01-13..01-16
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slides:none on file

Transforms X^n by the Kronecker power matrix F (Un = Xn F^{⊗m}) over GF(2) and proves the conditional entropies of U_i polarize to 0 or 1: for any fixed δ the fraction in (δ,1−δ)→0 as n→∞, and δ can shrink like exp(−√n). For source coding send the ~nH(X) high‑entropy coordinates; decoder reconstructs the rest with error ≤2^{−√n}. Binary‑input channel version yields synthetic bit‑channels with capacities near 0 or 1; encoding/decoding runs in about N log N.

AI-written summary · about

  1. 0:00Notation
  2. 2:40Source Polarization
  3. 21:50Source Code
  4. 33:40Questions
  5. 46:25Mutual Information
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