Renyi Entropy Rate of Stationary Ergodic Processes

Renyi entropy plays an important role in information theory and large deviation theory. For stochastic processes with good properties as mixing, Renyi entropy rate converges to the Shannon entropy rate. However, in this talk we will give an example to show that for general stationary and ergodic processes, the continuity of Renyi entropy rate breaks down at α=1. This is a joint work with Chengyu Wu, Li Xu and Guangyue Han.

More information about the Analysis Seminar can be found here.