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Lecture
Source Coding and Prefix-Free Codes
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Related lectures (28)
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Information Theory and Coding
Covers source coding, Kraft's inequality, mutual information, Huffman procedure, and properties of tropical sequences.
Information Theory: Source Coding & Channel Coding
Covers the fundamentals of information theory, focusing on source coding and channel coding.
Compression: Prefix-Free Codes
Explains prefix-free codes for efficient data compression and the significance of uniquely decodable codes.
Information Theory and Coding
Covers expected code word length, Huffman procedure, and entropy in coding theory.
Conditional Entropy and Data Compression Techniques
Discusses conditional entropy and its role in data compression techniques.
Compression: Kraft Inequality
Explains compression and Kraft inequality in codes and sequences.
Source Coding Theorem
Explores the Source Coding Theorem, entropy, Huffman coding, and conditioning's impact on entropy reduction.
Data Compression: Source Coding
Covers data compression techniques, including source coding and unique decodability concepts.
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.
Source Coding: Compression
Covers entropy, source coding, encoding maps, decodability, prefix-free codes, and Kraft-McMillan's inequality.
