Information Theory and Coding Basics

A binary source emits 0 with probability 0.9 and 1 with probability 0.1, independently. Take log₂ 0.9 ≈ −0.152 and log₂ 0.1 ≈ −3.32. Which of the following is closest to the entropy of this source?

  1. AAbout 0.14 bits
  2. BAbout 0.33 bits
  3. CAbout 0.47 bits
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Answer: C. About 0.47 bits

H = −0.9 × log₂ 0.9 − 0.1 × log₂ 0.1 ≈ 0.9 × 0.152 + 0.1 × 3.32 ≈ 0.137 + 0.332 ≈ 0.47 bits. If 0 and 1 were equally likely it would be 1 bit, but here a 0 is almost predictable, so the average information per symbol is less than half of that. A skewed source like this can, with clever coding, be represented with fewer than 1 bit per symbol.

  • A. About 0.14 is only the term for 0, −0.9 × log₂ 0.9; the term for 1 has not been added.
  • B. About 0.33 is only the term for 1, −0.1 × log₂ 0.1; the term for 0 has not been added.
  • C. Correct. Adding the two terms gives about 0.47 bits.
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  1. A source that emits 8 kinds of symbols has an entropy of 2.4 bits. Defining redundancy as 1 − (entropy ÷ maximum entropy), which of the following is the redundancy of this source?
  2. For two random variables X and Y, which of the following correctly describes the conditional entropy H(X|Y) and the mutual information I(X;Y)?
  3. Two random variables X (value 0 or 1) and Y (value a, b or c) have the joint probabilities P(0, a) = P(0, b) = P(1, b) = P(1, c) = 1/4, and every other combination has probability 0. Which of the following is the mutual information I(X;Y)?
  4. The 36 characters made up of the 26 capital letters and the 10 digits are to be distinguished by bit strings all of the same length (a fixed-length code). Which of the following is the minimum number of bits needed per character?
  5. Which of the following correctly describes a variable-length code compared with a fixed-length code?