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Lecture
Compression: Kraft Inequality
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Compression: Prefix-Free Codes
Explains prefix-free codes for efficient data compression and the significance of uniquely decodable codes.
Source Coding: Compression
Covers entropy, source coding, encoding maps, decodability, prefix-free codes, and Kraft-McMillan's inequality.
Composition of Applications in Mathematics
Explores the composition of applications in mathematics and the importance of understanding their properties.
Stochastic Processes: Sequences and Compression
Explores compression in stochastic processes through injective codes and prefix-free codes.
Compression: Prefix-free Codes
Explains how to design efficient prefix-free codes for compression.
Entropy and Algorithms: Applications in Sorting and Weighing
Covers the application of entropy in algorithms, focusing on sorting and decision-making strategies.
Mapping Functions and Surjections
Explores mapping functions, surjections, injective and surjective functions, and bijective functions.
Conditional Entropy and Data Compression Techniques
Discusses conditional entropy and its role in data compression techniques.
Information Theory: Source Coding & Channel Coding
Covers the fundamentals of information theory, focusing on source coding and channel coding.
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.
