Lecture: Shannon

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (27)

Page 1 of 3

Variational Formulation: Information Measures

Explores variational formulation for measuring information content and divergence between probability distributions.

Information Measures: Entropy and Information Theory

Explains how entropy measures uncertainty in a system based on possible outcomes.

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.

Information Theory: Source Coding, Cryptography, Channel Coding

Covers source coding, cryptography, and channel coding in communication systems, exploring entropy, codes, error channels, and future related courses.

Channel Coding: Convolutional Codes

Explores channel coding with a focus on convolutional codes, emphasizing error detection, correction, and decoding processes.

Entropy and Algorithms: Applications in Sorting and Weighing

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

Achievable Rate & Capacity

Explores achievable rate, channel capacity, spectral efficiency, and fading channels in wireless communication systems.

Quantifying Information: Probability, Entropy, and Constraints

Explores quantifying information based on probability, entropy, and constraints in communication systems.

Conditional Entropy and Information Theory Concepts

Discusses conditional entropy and its role in information theory and data compression.

Conditional Entropy and Data Compression Techniques

Discusses conditional entropy and its role in data compression techniques.