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Lecture
Shannon-Fano Codes
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Related lectures (24)
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Stochastic Processes: Sequences and Compression
Explores compression in stochastic processes through injective codes and prefix-free codes.
Compression: Kraft Inequality
Explains compression and Kraft inequality in codes and sequences.
Information Theory: Prefix-Free Codes
Covers prefix-free codes, Kraft inequality, Huffman coding, and entropy.
Data Compression and Shannon's Theorem: Entropy Calculation Example
Demonstrates the calculation of entropy for a specific example, resulting in an entropy value of 2.69.
Source Coding and Prefix-Free Codes
Covers source coding, injective codes, prefix-free codes, and Kraft's inequality.
Entropy and Data Compression: Huffman Coding Techniques
Discusses entropy, data compression, and Huffman coding techniques, emphasizing their applications in optimizing codeword lengths and understanding conditional entropy.
Kraft-McMillan Theorem
Explores the Kraft-McMillan theorem, proving the existence of uniquely decodable prefix-free codes.
Conditional Entropy: Huffman Coding
Explores conditional entropy and Huffman coding for efficient data compression techniques.
Shannon's Theorem
Introduces Shannon's Theorem on binary codes, entropy, and data compression limits.
Information Theory and Coding
Covers expected code word length, Huffman procedure, and entropy in coding theory.
