Relations between conditional Shannon entropy and expectation of ℓα-norm

The paper examines relationships between the conditional Shannon entropy and the expectation of ℓ_α-norm for joint probability distributions. More precisely, we investigate the sharp bounds of the expectation of ℓ_α-norm with a fixed conditional Shannon entropy, and vice versa. As applications of the results, we derive the sharp bounds between the conditional Shannon entropy and several information measures which are determined by the expectation of ℓ_α-norm, e.g., Arimoto's conditional Rényi entropy and the conditional R-norm information. Moreover, we apply these results to discrete memoryless channels under a uniform input distribution. Then, sharp bounds are obtained for Gallager's reliability functions E₀ with a fixed mutual information under a uniform input distribution.