Kraft-McMillan Theorem

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Related lectures (23)

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Source Coding: Compression

Covers entropy, source coding, encoding maps, decodability, prefix-free codes, and Kraft-McMillan's inequality.

Compression: Kraft Inequality

Explains compression and Kraft inequality in codes and sequences.

Compression: Prefix-Free Codes

Explains prefix-free codes for efficient data compression and the significance of uniquely decodable codes.

Conditional Entropy and Data Compression Techniques

Discusses conditional entropy and its role in data compression techniques.

Entropy and Algorithms: Applications in Sorting and Weighing

Covers the application of entropy in algorithms, focusing on sorting and decision-making strategies.

Shannon-Fano Codes

Covers Shannon-Fano codes, a method for uniquely decodable and prefix-free coding, and discusses their optimality compared to the entropy.

Compression: Strong Connection and Prefix-Free Codes

Explores the relationship between code word length and probability distribution, focusing on designing prefix-free codes for efficient compression.

Entropy and Algorithms: Twenty Questions Problem

Explores the Twenty Questions Problem, Huffman codes, and optimal querying strategies in algorithms, demonstrating efficient outcomes through prefix-free and ternary codes.

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.

Stochastic Processes: Sequences and Compression

Explores compression in stochastic processes through injective codes and prefix-free codes.