Practice Finding Optimal Encoding (21.9) - Greedy Algorithms: Huffman Codes

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9 questions

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6 sample questions

Question 1.
What is the purpose of Huffman encoding?
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Think about how we can use fewer bits.
Question 2.
Define the prefix property in encoding.
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Consider how Morse code can create ambiguity.
3Question 3.
What does Huffman coding primarily optimize in data transmission?
- Maximizes frequency of symbols
- Minimizes average bits per letter
- Increases binary code length
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Think about the purpose of compressing a message.
4Question 4.
True or False: In typically fixed-length encoding, all letters are represented by the same number of bits.
- True
- False
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Remember how each letter's length is consistent.
Question 5.
Create a Huffman tree for the characters: A, B, C, D, E with frequencies: A=0.5, B=0.25, C=0.15, D=0.05, and E=0.05. Explain the encoding process.
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Start with the smallest frequencies and merge.
Question 6.
Explain how combining nodes in a Huffman tree reduces average encoding lengths.
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Consider how many symbols are represented with fewer bits.

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