Uncertainty in Identification Systems

High-dimensional identification systems consisting of two groups users in the presence statistical uncertainties are considered this work. The task is to design enrollment mappings compress users' information and an mapping that combines stored database observation estimate underlying user index. compression-identification trade-off regions established for compound, extended general mixture settings. It shown several settings admit same trade-offs. We then study a connection between Wyner-Ahlswede-Körner network setting. indicates strong converse WAK equivalent Finally, we present arguments discrete setting extensible Gaussian scenario.