Hierarchical universal coding

Meir Feder*, Neri Merhav

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


In an earlier paper, we proved a strong version of the redundancy-capacity converse theorem of universal coding, stating that for "most" sources in a given class, the universal coding redundancy is essentially lower-bounded by the capacity of the channel induced by this class. Since this result holds for general classes of sources, it extends Rissanen's strong converse theorem for parametric families. While our earlier result has established strong optimality only for mixture codes weighted by the capacity-achieving prior, our first result herein extends this finding to a general prior. For some cases our technique also leads to a simplified proof of the above mentioned strong converse theorem. The major interest in this paper, however, is in extending the theory of universal coding to hierarchical structures of classes, where each class may have a different capacity. In this setting, one wishes to incur redundancy essentially as small as that corresponding to the active class, and not the union of classes. Our main result is that the redundancy of a code based on a two-stage mixture (first, within each class, and then over the classes), is no worse than that of any other code for "most" sources of "most" classes. If, in addition, the classes can be efficiently distinguished by a certain decision rule, then the best attainable redundancy is given explicitly by the capacity of the active class plus the normalized negative logarithm of the prior probability assigned to this class. These results suggest some interesting guidelines as for the choice of the prior. We also discuss some examples with a natural hierarchical partition into classes.

Original languageEnglish
Pages (from-to)1354-1364
Number of pages11
JournalIEEE Transactions on Information Theory
Issue number5
StatePublished - 1996


  • Arbitrarily varying sources
  • Capacity
  • Inaximin redundancy
  • Minimax redundancy
  • Mixtures
  • Redundancy-capacity theorem
  • Universal coding


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