Talk: Mr. Baohua Ni (September 06, 2023 at 4:30 PM, Zoom)
The Identification Capacity of the Modulo-Additive Noise Channel with Help
Mr. Baohua Ni
Signal and Information Processing Lab
ETH Zurich, Switzerland.
The gain in the Identification Capacity afforded by a rate-limited description of the noise sequence corrupting a modulo-additive noise channel is studied. Both the classical Ahlswede-Dueck version and the Ahlswede-Cai-Ning-Zhang version, which does not allow for missed identifications, are studied. Irrespective of whether the help is provided to the transmitter, to the receiver, or to both—the two capacities coincide and both equal the helper-assisted Shannon capacity.
Baohua Ni is a first-year doctoral student in the Signal and Information Processing Lab at ETH Zurich, under the guidance of Professor Amos Lapidoth. He graduated from the ITET department at ETH Zurich with Willi Studer Prize. His research interests center around traditional information theory and statistics, with a particular focus on guessing, identification, and hypothesis testing problems.