On estimating performance indices for biometric identification
Pattern Recognition
Special non-linear filter and extension to Shannon's channel capacity
Digital Signal Processing
A novel information transmission problem and its optimal solution
FCT'07 Proceedings of the 16th international conference on Fundamentals of Computation Theory
| Hi-index | 754.84 |
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 tests 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