Weighted least squares set estimation from l∞-normbounded noise data

The problem of parameter set estimation from pointwise bounded-error data is considered. The possibilities of employing l₂ -projection procedures to solve the problem are explored, and exact as well as approximate outer-bounding solutions are proposed. In particular, the properties of weighted least squares set estimation in this l_∞ norm bounded-error context and the implementation of a resulting minimum-volume parallelotope-bounding algorithm are discussed