7_HW7Solutions

7_HW7Solutions - c) To answer this question, it is most...

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1 EE 211A Digital Image Processing I Fall Quarter, 2011 Handout 23 Instructor: John Villasenor Homework 7 Solutions Solutions: 1. Symbol Code Prob 0 0 0 0.95 1 1 0.05 1 Entropy = Ave. length = Efficiency = 0.286 = 28.6% Symbol Code Prob 00 0 0.9025 0 1 01 10 0.0475 0 1 10 110 0.0475 0 1 11 111 0.0025 Entropy = 0.573, Ave. length = 0.9025 + 2(0.0475) + 3(0.0475) + 3(0.0025) = 1.147, Efficiency = 49%. 2. a) log 2 (k) b) The Huffman code achieves entropy when k = 2 n and 2 n+1 so L-H = 0 in either case.
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Unformatted text preview: c) To answer this question, it is most intuitive if we describe k as follows k = 2 n + m, where m is an offset from a power of two. m is in the range 0 m 2 n We can draw the Huffman tree for a uniform source as follows: m # codewords of length n # codewords of length n+1 1 15 2 2 14 4 3 13 6 2 So we now can describe the average length of a Huffman codeword as follows: Average Length = Total Bits / number of symbols Efficiency = Entropy / Average Length 3...
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This note was uploaded on 12/27/2011 for the course EE211A 211A taught by Professor Villasenor during the Fall '11 term at UCLA.

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7_HW7Solutions - c) To answer this question, it is most...

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