A General Formula for Channel Capacity

Sergio Verdú, Te Sun Han

Research output: Contribution to journalArticlepeer-review

547 Scopus citations


A formula for the capacity of arbitrary single-user channels without feedback (not necessarily information stable, stationary, etc.) is proved. Capacity is shown to equal the supremum, over all input processes, of the input-output inf - information rate defined as the liminf in probability of the normalized information density. The key to this result is a new converse approach based on a simple new lower bound on the error probability of m-ary hypothesis testa among equiprobable hypotheses. A necessary and sufficient condition for the validity of the strong converse is given, as well as general expressions for ε-capacity.

Original languageEnglish (US)
Pages (from-to)1147-1157
Number of pages11
JournalIEEE Transactions on Information Theory
Issue number4
StatePublished - Jul 1994

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


  • Shannon theory
  • channel capacity
  • channel coding theorem
  • channels with memory
  • strong converse


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