Generalized source coding theorems and hypothesis testing: Part II - Operational limits

Abstract

In light of the information measures introduced in Part I, a generalized version of the Asymptotic Equipartition Property (AEP) is proved, General fixed-length data compaction and data compression (source coding) theorems for arbitrary finite-alphabet sources are also established, Finally, the general expression of the Neyman-Pearson type-II error exponent subject to upper bounds on the type-I error probability is examined.