Information Theory: Quantifying Messages and Source Entropy

This lecture introduces the concept of quantifying information based on the probability of occurrence in messages, emphasizing the importance of quantifying information in communication systems. It covers the minimum number of bits required to store digital messages, the entropy of a source, and the maximum entropy distributions under different constraints. The lecture also explores the calculation of common information between random sources and the communication channel capacity in the presence of noise, highlighting the significance of the signal-to-noise ratio in determining the transmission channel's capacity.