Data Compression and Shannon's Theorem: Recap

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Data Compression and Shannon's Theorem: Shannon-Fano Coding

Explores Shannon-Fano coding for efficient data compression and its comparison to Huffman coding.

Data Compression and Shannon's Theorem: Huffman Codes

Explores the performance of Shannon-Fano algorithm and introduces Huffman codes for efficient data compression.

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 Theorem

Explores the Source Coding Theorem, entropy, Huffman coding, and conditioning's impact on entropy reduction.

Conditional Entropy and Data Compression Techniques

Discusses conditional entropy and its role in data compression techniques.

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.

Data Compression and Entropy 2: Entropy as 'Question Game'

Explores entropy as a 'question game' to guess letters efficiently and its relation to data compression.

Data Compression and Entropy: Compression

Explores lossless data compression techniques, emphasizing efficient message representation and encoding strategies.

Data Compression and Shannon Fano Coding

Explores practical data compression using Shannon Fano coding and the engineering challenges of compressing diverse data types.

Lossless Compression: Shannon-Fano and Huffman

Explores lossless compression using Shannon-Fano and Huffman algorithms, showcasing Huffman's superior efficiency and speed over Shannon-Fano.