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(IC 3.1) Entropy as a lower bound on expected length (part 1)
(IC 2.10) Kraft-McMillan - examples for (b)
(IC 2.3) Symbol codes - definition and examples
(IC 4.5) An issue with Huffman coding
(IC 3.2) Entropy as a lower bound on expected length (part 2)
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Last Updated: September 28, 2026
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Summary
Using Shannon coding, one can get within 1 of the entropy. This gives an upper bound on the Basic definitions for symbol codes (a.k.a. variable- We prove that Huffman codes are optimal. In part 1, we show that the Huffman coding does not work well when the source has low entropy, since