Capacity of steganographic channels
MM&Sec '05 Proceedings of the 7th workshop on Multimedia and security
Reliability criteria in information theory and in statistical hypothesis testing
Foundations and Trends in Communications and Information Theory
Detection of Gauss-Markov random fields with nearest-neighbor dependency
IEEE Transactions on Information Theory
Capacity of steganographic channels
IEEE Transactions on Information Theory
Discrimination of two channels by adaptive methods and its application to quantum system
IEEE Transactions on Information Theory
Detection error exponent for spatially dependent samples in random networks
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
On logarithmically asymptotically optimal testing of hypotheses and identification
General Theory of Information Transfer and Combinatorics
Multiple objects: error exponents in hypotheses testing and identification
Information Theory, Combinatorics, and Search Theory
| Hi-index | 755.02 |
The asymptotically optimal hypothesis testing problem, with general sources as the null and alternative hypotheses, is studied under exponential-type error constraints on the first kind of error probability. Our fundamental philosophy is to convert all of the hypothesis testing problems to the pertinent computation problems in the large deviation-probability theory. This methodologically new approach enables us to establish compact general formulas of the optimal exponents of the second kind of error and correct testing probabilities for the general sources including all nonstationary and/or nonergodic sources with arbitrary abstract alphabet (countable or uncountable). These general formulas are presented from the information-spectrum point of view