2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | S.5.1 | ||
| Paper Title | The Asymptotic Generalized Poor-Verdú Bound Achieves the BSC Error Exponent at Zero Rate | ||
| Authors | Ling-Hua Chang, Yuan-Ze University, Taiwan; Po-Ning Chen, Chiao Tung University, Taiwan; Fady Alajaji, Queen's university, Canada; Yunghsiang S. Han, Dongguan University of Technology, China | ||
| Session | S.5: Error Exponents | ||
| Presentation | Lecture | ||
| Track | Shannon Theory | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | The generalized Poor-Verdu error lower bound for multihypothesis testing is revisited. Its asymptotic expressionis established in closed-form as its tilting parameter grows to infinity. It is also shown that the asymptotic generalized bound achieves the error exponent (or reliability function) of the memoryless binary symmetric channel at zero coding rates. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
