  This paper addresses the classical problem of determining the set of possible
states of a linear discrete-time system subject to bounded disturbances from
measurements corrupted by bounded noise. These so-called uncertainty sets
evolve with time as new measurements become available. We present two theorems
which describe completely how they evolve with time, and this yields an
efficient algorithm for recursively updating uncertainty sets. Numerical
simulations demonstrate performance improvements over existing exact methods.
