Informational divergence and entropy rate on rooted trees with probabilities

Rooted trees with probabilities are used to analyze properties of variable length codes. A bound is derived on the difference between the entropy rates of such codes and memoryless sources. The bound is in terms of normalized informational divergence and is used to derive converses for exact random number generation, resolution coding, and distribution matching.