Title :
Weighted least squares set estimation from l∞-norm bounded noise data
Author_Institution :
Dept. of Agric. Eng. & Phys., Wageningen Agric. Univ., Netherlands
fDate :
10/1/1997 12:00:00 AM
Abstract :
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
Keywords :
error analysis; least squares approximations; parameter estimation; set theory; approximate outer-bounding; l∞-norm bounded noise data; parallelotopes; parameter set estimation; pointwise bounded-error data; set membership identification; weighted least squares; Agricultural engineering; Algorithm design and analysis; Colored noise; Equations; Least squares approximation; Least squares methods; Measurement uncertainty; Noise measurement; Parameter estimation; Physics;
Journal_Title :
Automatic Control, IEEE Transactions on
