hw9_source_coding

# hw9_source_coding - MASSACHUSETTS INSTITUTE OF TECHNOLOGY...

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6.02 Spring 2008 1 of 3 HW #9 M ASSACHUSETTS I NSTITUTE OF T ECHNOLOGY D EPARTMENT OF E LECTRICAL E NGINEERING AND C OMPUTER S CIENCE 6.02 Introduction to EECS II Spring 2008 Homework #9: Source Coding Issued: April 11, 2008 Due: April 18, 2008 Problem 1. Huffman and other coding schemes tend to devote more bits to the coding of (choose one): (A) symbols carrying the most information (B) symbols carrying the least information (C) symbols that are likely to be repeated consecutively (D) symbols containing redundant information Problem 2. Consider the following two Huffman decoding tress for a variable-length code involving 5 symbols: A, B, C, D and E. (A) Using Tree #1, decode the following encoded message: "01000111101". (B) S uppose we were encoding messages with the following probabilities for each of the 5 symbols: p(A) = 0.5, p(B) = p(C) = p(D) = p(E) = 0.125. Which of the two encodings above (Tree #1 or Tree #2) would yield the shortest encoded messages averaged over many messages? (C) Using the probabilities for A, B, C, D and E given in part (B), construct a variable- length binary decoding tree using the simple greedy algorithm presented in lecture: 1. Begin with the set S of symbols to be encoded as binary strings, together with the probability P(x) for each symbol x. The probabilities sum to 1 and measure the frequencies with which each symbol appears in the input stream. In this example,

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## This note was uploaded on 08/23/2009 for the course EECS 6.02 taught by Professor Terman during the Spring '08 term at MIT.

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hw9_source_coding - MASSACHUSETTS INSTITUTE OF TECHNOLOGY...

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