Abstract
The Fano inequality gives a lower bound on the mutual information between two random variables that take values on an M-element set, provided at least one of the random variables is equiprobable. We show several simple lower bounds on mutual information which do not assume such a restriction. In particular, this can be accomplished by replacing log M with the infinite-order Renyi entropy in the Fano inequality. Applications to hypothesis testing are exhibited along with bounds on mutual information in terms of the a priori and a posteriori error probabilities.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1247-1251 |
| Number of pages | 5 |
| Journal | IEEE Transactions on Information Theory |
| Volume | 40 |
| Issue number | 4 |
| DOIs | |
| State | Published - Jul 1994 |
All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Science Applications
- Library and Information Sciences
Keywords
- Fano inequality
- Shannon theory
- hypothesis testing
- mutual information
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