Weighted least squares set estimation from l/sub ∞/-norm bounded noise data

Abstract

The problem of parameter set estimation from pointwise bounded-error data is considered. The possibilities of employing l/sub 2/-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/sub /spl infin// norm bounded-error context and the implementation of a resulting minimum-volume parallelotope-bounding algorithm are discussed.