Skip to main content
Graph
Search
fr
|
en
Switch to dark mode
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Source Coding Theorem
Graph Chatbot
Related lectures (26)
Previous
Page 1 of 3
Next
Conditional Entropy and Data Compression Techniques
Discusses conditional entropy and its role in data compression techniques.
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.
Compression: Prefix-Free Codes
Explains prefix-free codes for efficient data compression and the significance of uniquely decodable codes.
Data Compression and Shannon-Fano Algorithm
Explores the Shannon-Fano algorithm for data compression and its efficiency in creating unique binary codes for letters.
Source Coding Theorems: Entropy and Source Models
Covers source coding theorems, entropy, and various source models in information theory.
Entropy and Algorithms: Applications in Sorting and Weighing
Covers the application of entropy in algorithms, focusing on sorting and decision-making strategies.
Conditional Entropy: Huffman Coding
Explores conditional entropy and Huffman coding for efficient data compression techniques.
Data Compression and Shannon's Theorem Summary
Summarizes Shannon's theorem, emphasizing the importance of entropy in data compression.
Conditional Entropy and Information Theory Concepts
Discusses conditional entropy and its role in information theory and data compression.
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.
